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@article{_cellular_????,
title = {Cellular Population Dynamics Control the Robustness of the Stem Cell Niche},
journaltitle = {Biology Open},
issn = {2046-6390},
doi = {10.1242/bio.013714},
url = {http://bio.biologists.org/content/early/2015/10/02/bio.013714.abstract},
abstract = {ABSTRACTWithin populations of cells, fate decisions are controlled by an indeterminate combination of cell-intrinsic and cell-extrinsic factors. In the case of stem cells, the stem cell niche is believed to maintain ‘stemness' through communication and interactions between the stem cells and one or more other cell-types that contribute to the niche conditions. To investigate the robustness of cell fate decisions in the stem cell hierarchy and the role that the niche plays, we introduce simple mathematical models of stem and progenitor cells, their progeny and their interplay in the niche. These models capture the fundamental processes of proliferation and differentiation and allow us to consider alternative possibilities regarding how niche-mediated signalling feedback regulates the niche dynamics. Generalised stability analysis of these stem cell niche systems enables us to describe the stability properties of each model. We find that although the number of feasible states depends on the model, their probabilities of stability in general do not: stem cell–niche models are stable across a wide range of parameters. We demonstrate that niche-mediated feedback increases the number of stable steady states, and show how distinct cell states have distinct branching characteristics. The ecological feedback and interactions mediated by the stem cell niche thus lend (surprisingly) high levels of robustness to the stem and progenitor cell population dynamics. Furthermore, cell–cell interactions are sufficient for populations of stem cells and their progeny to achieve stability and maintain homeostasis. We show that the robustness of the niche – and hence of the stem cell pool in the niche – depends only weakly, if at all, on the complexity of the niche make-up: simple as well as complicated niche systems are capable of supporting robust and stable stem cell dynamics.}
}
@online{08RosettesJupyterNotebook,
title = {08-{{Rosettes}} - {{Jupyter Notebook}}},
url = {http://localhost:8888/notebooks/tyssue-demo/08-Rosettes.ipynb#},
urldate = {2021-02-10},
file = {/home/guillaume/Zotero/storage/BAXALMZW/08-Rosettes.html}
}
@article{aidukasLowcostSubmicronResolution2019,
title = {Low-Cost, Sub-Micron Resolution, Wide-Field Computational Microscopy Using Opensource Hardware},
author = {Aidukas, Tomas and Eckert, Regina and Harvey, Andrew R. and Waller, Laura and Konda, Pavan C.},
date = {2019-05-15},
journaltitle = {Scientific Reports},
volume = {9},
number = {1},
pages = {7457},
issn = {2045-2322},
doi = {10.1038/s41598-019-43845-9},
url = {https://www.nature.com/articles/s41598-019-43845-9},
urldate = {2019-05-18},
abstract = {The revolution in low-cost consumer photography and computation provides fertile opportunity for a disruptive reduction in the cost of biomedical imaging. Conventional approaches to low-cost microscopy are fundamentally restricted, however, to modest field of view (FOV) and/or resolution. We report a low-cost microscopy technique, implemented with a Raspberry Pi single-board computer and color camera combined with Fourier ptychography (FP), to computationally construct 25-megapixel images with sub-micron resolution. New image-construction techniques were developed to enable the use of the low-cost Bayer color sensor, to compensate for the highly aberrated re-used camera lens and to compensate for misalignments associated with the 3D-printed microscope structure. This high ratio of performance to cost is of particular interest to high-throughput microscopy applications, ranging from drug discovery and digital pathology to health screening in low-income countries. 3D models and assembly instructions of our microscope are made available for open source use.},
langid = {english},
file = {/home/guillaume/Zotero/storage/FCGG7I6P/Aidukas et al. - 2019 - Low-cost, sub-micron resolution, wide-field comput.pdf;/home/guillaume/Zotero/storage/66S87H5C/s41598-019-43845-9.html}
}
@article{aigouy_suppplemental_2007,
title = {Suppplemental Data {{The Influence}} of {{Cell Mechanics}}, {{Cell}}-{{Cell Interactions}}, and {{Proliferation}} on {{Epithelial Packing}}},
author = {Aigouy, Benoit and Farhadifar, Reza and Ro, Jens-christian and Eaton, Suzanne and Ju, Frank and Results, Supplemental and Ablation, Laser},
date = {2007},
journaltitle = {Current Biology},
pages = {1--9},
file = {/home/guillaume/Zotero/storage/79CZKFJW/Aigouy et al. - 2007 - Suppplemental data The Influence of Cell Mechanics, Cell-Cell Interactions, and Proliferation on Epithelial Packi.pdf}
}
@article{aigouyCellFlowReorients2010,
title = {Cell {{Flow Reorients}} the {{Axis}} of {{Planar Polarity}} in the {{Wing Epithelium}} of {{Drosophila}}},
author = {Aigouy, Benoît and Farhadifar, Reza and Staple, Douglas B. and Sagner, Andreas and Röper, Jens-Christian and Jülicher, Frank and Eaton, Suzanne},
date = {2010-09-03},
journaltitle = {Cell},
volume = {142},
number = {5},
pages = {773--786},
issn = {0092-8674},
doi = {10.1016/j.cell.2010.07.042},
url = {https://www.sciencedirect.com/science/article/pii/S0092867410008901},
urldate = {2021-04-15},
abstract = {Planar cell polarity (PCP) proteins form polarized cortical domains that govern polarity of external structures such as hairs and cilia in both vertebrate and invertebrate epithelia. The mechanisms that globally orient planar polarity are not understood, and are investigated here in the Drosophila wing using a combination of experiment and theory. Planar polarity arises during growth and PCP domains are initially oriented toward the well-characterized organizer regions that control growth and patterning. At pupal stages, the wing hinge contracts, subjecting wing-blade epithelial cells to anisotropic tension in the proximal-distal axis. This results in precise patterns of oriented cell elongation, cell rearrangement and cell division that elongate the blade proximo-distally and realign planar polarity with the proximal-distal axis. Mutation of the atypical Cadherin Dachsous perturbs the global polarity pattern by altering epithelial dynamics. This mechanism utilizes the cellular movements that sculpt tissues to align planar polarity with tissue shape.},
langid = {english},
keywords = {DEVBIO},
file = {/home/guillaume/Zotero/storage/4PT9UVG4/Aigouy et al. - 2010 - Cell Flow Reorients the Axis of Planar Polarity in.pdf;/home/guillaume/Zotero/storage/LW5PW2NQ/S0092867410008901.html}
}
@article{albeckCollectingOrganizingSystematic2006,
title = {Collecting and Organizing Systematic Sets of Protein Data},
author = {Albeck, John G. and MacBeath, Gavin and White, Forest M. and Sorger, Peter K. and Lauffenburger, Douglas A. and Gaudet, Suzanne},
date = {2006-11},
journaltitle = {Nature Reviews Molecular Cell Biology},
volume = {7},
number = {11},
pages = {803--812},
issn = {1471-0072, 1471-0080},
doi = {10.1038/nrm2042},
url = {http://www.nature.com/doifinder/10.1038/nrm2042},
urldate = {2016-11-02}
}
@article{aldridgePhysicochemicalModellingCell2006,
title = {Physicochemical Modelling of Cell Signalling Pathways},
author = {Aldridge, Bree B. and Burke, John M. and Lauffenburger, Douglas A. and Sorger, Peter K.},
date = {2006-11},
journaltitle = {Nat Cell Biol},
volume = {8},
number = {11},
pages = {1195--1203},
issn = {1465-7392},
doi = {10.1038/ncb1497},
url = {http://www.nature.com/ncb/journal/v8/n11/abs/ncb1497.html},
urldate = {2016-11-02},
abstract = {Physicochemical modelling of signal transduction links fundamental chemical and physical principles, prior knowledge about regulatory pathways, and experimental data of various types to create powerful tools for formalizing and extending traditional molecular and cellular biology.},
langid = {english},
file = {/home/guillaume/Zotero/storage/AG3NTATQ/ncb1497.html}
}
@article{aleciNovelCheapMethod2018,
title = {A Novel and Cheap Method to Correlate Subjective and Objective Visual Acuity by Using the Optokinetic Response},
author = {Aleci, Carlo and Scaparrotti, Martina and Fulgori, Sabrina and Canavese, Lorenzo},
date = {2018-10-01},
journaltitle = {Int Ophthalmol},
volume = {38},
number = {5},
pages = {2101--2115},
issn = {1573-2630},
doi = {10.1007/s10792-017-0709-x},
url = {https://doi.org/10.1007/s10792-017-0709-x},
urldate = {2019-03-13},
abstract = {PurposeTo describe a novel optokinetic visual acuity estimator (Oktotype) and to report the preliminary results obtained in poorly and non-collaborative subjects.MethodsEleven series of symbols arranged horizontally and moving from left to right at a constant rate were displayed. In each sequence, the size of the stimuli was reduced logarithmically. By using this paradigm, the objective visual acuity was computed in 26 normal subjects as the minimum size of the symbols able to evoke the optokinetic response. In the preliminary phase, three contrast levels were tested, with white noise added to the first five sequences so as to normalize the overestimate found at the lower-half range of the acuity scale. Subsequently, the correspondence between subjective and objective visual acuity was compared in 10 poorly collaborative subjects, and the agreement between optokinetic and Teller visual acuity was measured in six non-collaborative subjects.ResultsThe best agreement is provided by the minimum contrast level (20\%) (R 2 = 0.74). The correspondence between the two techniques is satisfying both in the normal and in the poorly collaborative sample (concordance correlation coefficient: 0.85 and 0.83, respectively). In the non-collaborative group, the concordance correlation coefficient between Teller acuity and OKVA ranged between 0.79 (test) and 0.85 (retest). Test–retest reliability was very good for the Oktotype (K: 0.82), and better than the Teller test (K = 0.71), even if it was lower compared to Snellen acuity (K = 0.95).ConclusionThe Oktotype seems promising to predict Snellen visual acuity in normal and poorly collaborative subjects.},
langid = {english},
keywords = {Agreement,Non-collaborative patients,Oktotype,Optokinetic nystagmus,Teller cards,Test–retest reliability,Visual acuity}
}
@article{aleciOptokineticResponseEffective2018,
title = {The Optokinetic Response Is Effective to Assess Objective Visual Acuity in Patients with Cataract and Age-Related Macular Degeneration},
author = {Aleci, Carlo and Cossu, Gabriele and Belcastro, Elena and Canavese, Lorenzo},
date = {2018-08-14},
journaltitle = {Int Ophthalmol},
issn = {1573-2630},
doi = {10.1007/s10792-018-1001-4},
url = {https://doi.org/10.1007/s10792-018-1001-4},
urldate = {2019-03-13},
abstract = {PurposeTo estimate objective visual acuity in subjects suffering from cataract and age-related macular degeneration via the optokinetic response evoked by a non-conventional induction method (oktotype); in addition, to compare such objective outcome with the subjective acuity based on the ETDRS charts.MethodsPatients were presented with 13 sequences of symbols arranged horizontally to form a serial pattern, moving from left to right at a constant rate. In each sequence, the size of the stimuli was reduced progressively, while the operator checked for the disappearance of the optokinetic response via a small video camera mounted on the test lens frame. The minimum angular size of the serial pattern able to evoke the optokinetic response (MAER) was referred to as the objective visual acuity of the subject.ResultsCorrelation between logMAER and logMAR was significant in the cataract and macular degeneration group (𝑅2catRcat2R\_\{\textbackslash text\{cat\}\}\^\{2\} = 0.70, p {$<$} .0001; 𝑅2AMDRAMD2R\_\{\textbackslash text\{AMD\}\}\^\{2\} = 0.63, p {$<$} .0007). In the two samples, the correspondence between subjective and objective visual acuity (as, respectively, decimal units and arbitrary decimal units) was satisfactory (concordance correlation coefficient: cataract group = 0.91 and AMD group = 0.93). Test–retest reliability of the oktotype was good for the cataract group and moderate for the AMD sample (Κ 0.81 and 0.59, respectively).ConclusionThe oktotype seems a promising tool to objectively assess visual acuity in noncooperating subjects with cataract or macular degeneration. Further research on other clinical conditions is needed to clarify the suitability of the procedure in the clinical setting.},
langid = {english},
keywords = {Age-related macular degeneration,Cataract,Oktotype,Optokinetic nystagmus,Test–retest reliability,Visual acuity}
}
@article{alegotJakStatPathwayInduces2018,
title = {Jak-{{Stat}} Pathway Induces {{Drosophila}} Follicle Elongation by a Gradient of Apical Contractility},
author = {Alégot, Hervé and Pouchin, Pierre and Bardot, Olivier and Mirouse, Vincent},
editor = {Knust, Elisabeth},
date = {2018-02-08},
journaltitle = {eLife},
volume = {7},
pages = {e32943},
issn = {2050-084X},
doi = {10.7554/eLife.32943},
url = {https://doi.org/10.7554/eLife.32943},
urldate = {2020-01-15},
abstract = {Tissue elongation and its control by spatiotemporal signals is a major developmental question. Currently, it is thought that Drosophila ovarian follicular epithelium elongation requires the planar polarization of the basal domain cytoskeleton and of the extra-cellular matrix, associated with a dynamic process of rotation around the anteroposterior axis. Here we show, by careful kinetic analysis of fat2 mutants, that neither basal planar polarization nor rotation is required during a first phase of follicle elongation. Conversely, a JAK-STAT signaling gradient from each follicle pole orients early elongation. JAK-STAT controls apical pulsatile contractions, and Myosin II activity inhibition affects both pulses and early elongation. Early elongation is associated with apical constriction at the poles and with oriented cell rearrangements, but without any visible planar cell polarization of the apical domain. Thus, a morphogen gradient can trigger tissue elongation through a control of cell pulsing and without a planar cell polarity requirement.},
keywords = {dynamics,morphogen,morphogenesis},
file = {/home/guillaume/Zotero/storage/V2DDIQ7R/Alégot et al. - 2018 - Jak-Stat pathway induces Drosophila follicle elong.pdf}
}
@article{aliee_physical_2012,
title = {Physical Mechanisms Shaping the {{Drosophila}} Dorsoventral Compartment Boundary},
author = {Aliee, Maryam and Röper, Jens Christian and Landsberg, Katharina P. and Pentzold, Constanze and Widmann, Thomas J. and Jülicher, Frank and Dahmann, Christian},
date = {2012},
journaltitle = {Current Biology},
volume = {22},
number = {11},
eprint = {22560616},
eprinttype = {pmid},
pages = {967--976},
issn = {09609822},
doi = {10.1016/j.cub.2012.03.070},
abstract = {Background: Separating cells with distinct identities and fates by straight and sharp compartment boundaries is important for growth and pattern formation during animal development. The physical mechanisms shaping compartment boundaries, however, are not fully understood. Results: We combine theory and quantitative experiments to investigate the roles of different mechanisms to shape compartment boundaries. Our theoretical work shows that cell elongation created by anisotropic stress, cell proliferation rate, orientation of cell division, and cell bond tension all have distinct effects on the morphology of compartment boundaries during tissue growth. Our experiments using the developing Drosophila wing reveal that the roughness of the dorsoventral compartment boundary is dynamic and that it decreases during development. By measuring tissue relaxation in response to laser ablation of cell bonds at different developmental times, we demonstrate that decreased boundary roughness correlates with increased cell bond tension along the compartment boundary. Finally, by using experimentally determined values for cell bond tension, cell elongation and bias in orientation of cell division in simulations of tissue growth, we can reproduce the main features of the time evolution of the dorsoventral compartment boundary shape. Conclusions: Local increase of cell bond tension along the boundary as well as global anisotropies in the tissue contribute to shaping boundaries in cell networks. We propose a simple scenario that combines time-dependent cell bond tension at the boundary, oriented cell division, and cell elongation in the tissue that can account for the main features of the dynamics of the shape of the dorsoventral compartment boundary. © 2012 Elsevier Ltd.},
file = {/home/guillaume/Zotero/storage/8NGIH63C/Aliee et al. - 2012 - Physical mechanisms shaping the Drosophila dorsoventral compartment boundary.pdf}
}
@article{aliee_supplemental_????,
title = {Supplemental {{Information Physical Mechanisms Shaping}} The},
author = {Aliee, Maryam and Landsberg, Katharina P and Pentzold, Constanze and Widmann, Thomas J and Dahmann, Christian and Inventory, Supplemental},
volume = {22},
file = {/home/guillaume/Zotero/storage/AFQZI3WE/Aliee et al. - Unknown - Supplemental Information Physical Mechanisms Shaping the.pdf}
}
@article{allenaDiffusionreactionModelDrosophila2013,
title = {Diffusion-Reaction Model for {{Drosophila}} Embryo Development},
author = {Allena, R. and Muñoz, J. J. and Aubry, D.},
date = {2013-03-01},
journaltitle = {Computer Methods in Biomechanics and Biomedical Engineering},
volume = {16},
number = {3},
eprint = {21970322},
eprinttype = {pmid},
pages = {235--248},
issn = {1025-5842},
doi = {10.1080/10255842.2011.616944},
url = {http://dx.doi.org/10.1080/10255842.2011.616944},
urldate = {2017-03-06},
abstract = {During the early stages of gastrulation in Drosophila embryo, the epithelial cells composing the single tissue layer of the egg undergo large strains and displacements. These movements have been usually modelled by decomposing the total deformation gradient in an (imposed or strain/stress dependent) active part and a passive response. Although the influence of the chemical and genetic activity in the mechanical response of the cell has been experimentally observed, the effects of the mechanical deformation on the latter have been far less studied, and much less modelled. Here, we propose a model that couples morphogen transport and the cell mechanics during embryogenesis. A diffusion-reaction equation is introduced as an additional mechanical regulator of morphogenesis. Consequently, the active deformations are not directly imposed in the analytical formulation, but they rather depend on the morphogen concentration, which is introduced as a new variable. In this study, we show that strain patterns similar to those observed during biological experiments can be reproduced by properly combining the two phenomena. In addition, we use a novel technique to parameterise the embryo geometry by solving two Laplace problems with specific boundary conditions. We apply the method to two morphogenetic movements: ventral furrow invagination and germ band extension. The matching between our results and the observed experimental deformations confirms that diffusion-reaction of morphogens can actually be controlling large morphogenetic movements.},
keywords = {cell mechanics,diffusion-reaction,finite element model,Morphogenesis},
file = {/home/guillaume/Zotero/storage/ARWFR5IX/allena2013.pdf;/home/guillaume/Zotero/storage/QC4W7AA4/10255842.2011.html}
}
@article{allenaDiffusionreactionModelDrosophila2013a,
title = {Diffusion-Reaction Model for {{Drosophila}} Embryo Development},
author = {Allena, R. and Muñoz, J. J. and Aubry, D.},
date = {2013-03-01},
journaltitle = {Computer Methods in Biomechanics and Biomedical Engineering},
volume = {16},
number = {3},
eprint = {21970322},
eprinttype = {pmid},
pages = {235--248},
issn = {1025-5842},
doi = {10.1080/10255842.2011.616944},
url = {http://dx.doi.org/10.1080/10255842.2011.616944},
urldate = {2017-03-06},
abstract = {During the early stages of gastrulation in Drosophila embryo, the epithelial cells composing the single tissue layer of the egg undergo large strains and displacements. These movements have been usually modelled by decomposing the total deformation gradient in an (imposed or strain/stress dependent) active part and a passive response. Although the influence of the chemical and genetic activity in the mechanical response of the cell has been experimentally observed, the effects of the mechanical deformation on the latter have been far less studied, and much less modelled. Here, we propose a model that couples morphogen transport and the cell mechanics during embryogenesis. A diffusion-reaction equation is introduced as an additional mechanical regulator of morphogenesis. Consequently, the active deformations are not directly imposed in the analytical formulation, but they rather depend on the morphogen concentration, which is introduced as a new variable. In this study, we show that strain patterns similar to those observed during biological experiments can be reproduced by properly combining the two phenomena. In addition, we use a novel technique to parameterise the embryo geometry by solving two Laplace problems with specific boundary conditions. We apply the method to two morphogenetic movements: ventral furrow invagination and germ band extension. The matching between our results and the observed experimental deformations confirms that diffusion-reaction of morphogens can actually be controlling large morphogenetic movements.},
keywords = {cell mechanics,diffusion-reaction,finite element model,Morphogenesis},
file = {/home/guillaume/Zotero/storage/R6WWJWF7/10255842.2011.html}
}
@article{allenaSimulationMultipleMorphogenetic2010,
title = {Simulation of Multiple Morphogenetic Movements in the {{Drosophila}} Embryo by a Single {{3D}} Finite Element Model},
author = {Allena, R. and Mouronval, A. -S. and Aubry, D.},
date = {2010-05-01},
journaltitle = {Journal of the Mechanical Behavior of Biomedical Materials},
volume = {3},
number = {4},
pages = {313--323},
issn = {1751-6161},
doi = {10.1016/j.jmbbm.2010.01.001},
url = {http://www.sciencedirect.com/science/article/pii/S1751616110000032},
urldate = {2017-07-12},
abstract = {The present work describes a 3D finite element model of the Drosophila embryo designed to simulate three morphogenetic movements during early gastrulation: ventral furrow invagination, cephalic furrow formation and germ band extension. The embryo is represented by a regular ellipsoid and only the mesoderm is modeled. Additionally, the parametric description of the biological structure in a special curvilinear system provides mesh-independent endogenous strains. A deformation gradient decomposition is used to couple an active deformation, specific for each morphogenetic movement, together with a passive deformation, which is due to the response of the continuous mesoderm. Boundary conditions such as the rigid contact with the external vitelline membrane and the yolk pressure are also taken into account. The results suggest that the number of active strains responsible for the morphogenetic events can be less than that deduced from direct experimental observations. Finally, the estimation of the non-local pressures induced during morphogenetic movements is in good agreement with the experimental data.},
file = {/home/guillaume/Zotero/storage/CT9QSMXT/S1751616110000032.html}
}
@article{altrockMathematicsCancerIntegrating2015,
title = {The Mathematics of Cancer: Integrating Quantitative Models},
shorttitle = {The Mathematics of Cancer},
author = {Altrock, Philipp M. and Liu, Lin L. and Michor, Franziska},
date = {2015-12},
journaltitle = {Nat. Rev. Cancer},
volume = {15},
number = {12},
eprint = {26597528},
eprinttype = {pmid},
pages = {730--745},
issn = {1474-1768},
doi = {10.1038/nrc4029},
abstract = {Mathematical modelling approaches have become increasingly abundant in cancer research. The complexity of cancer is well suited to quantitative approaches as it provides challenges and opportunities for new developments. In turn, mathematical modelling contributes to cancer research by helping to elucidate mechanisms and by providing quantitative predictions that can be validated. The recent expansion of quantitative models addresses many questions regarding tumour initiation, progression and metastases as well as intra-tumour heterogeneity, treatment responses and resistance. Mathematical models can complement experimental and clinical studies, but also challenge current paradigms, redefine our understanding of mechanisms driving tumorigenesis and shape future research in cancer biology.},
langid = {english},
keywords = {Animals,Cancer genetics,Cancer microenvironment,Cancer models,Cancer therapy,Computational biology and bioinformatics,Disease Progression,Humans,Metastasis,Models; Biological,Models; Theoretical,Neoplasms,Prognosis},
file = {/home/guillaume/Zotero/storage/RP4P73BS/nrc4029.html}
}
@article{anApicalConstrictionDriven2017,
title = {Apical Constriction Is Driven by a Pulsatile Apical Myosin Network in Delaminating {{{\emph{Drosophila}}}} Neuroblasts},
author = {An, Yanru and Xue, Guosheng and Shaobo, Yang and Mingxi, Deng and Zhou, Xiaowei and Yu, Weichuan and Ishibashi, Toyotaka and Zhang, Lei and Yan, Yan},
date = {2017-06-15},
journaltitle = {Development},
volume = {144},
number = {12},
eprint = {28506995},
eprinttype = {pmid},
pages = {2153--2164},
issn = {0950-1991, 1477-9129},
doi = {10.1242/dev.150763},
url = {http://dev.biologists.org/content/144/12/2153},
urldate = {2017-06-21},
abstract = {Skip to Next Section Cell delamination is a conserved morphogenetic process important for the generation of cell diversity and maintenance of tissue homeostasis. Here, we used Drosophila embryonic neuroblasts as a model to study the apical constriction process during cell delamination. We observe dynamic myosin signals both around the cell adherens junctions and underneath the cell apical surface in the neuroectoderm. On the cell apical cortex, the nonjunctional myosin forms flows and pulses, which are termed medial myosin pulses. Quantitative differences in medial myosin pulse intensity and frequency are crucial to distinguish delaminating neuroblasts from their neighbors. Inhibition of medial myosin pulses blocks delamination. The fate of a neuroblast is set apart from that of its neighbors by Notch signaling-mediated lateral inhibition. When we inhibit Notch signaling activity in the embryo, we observe that small clusters of cells undergo apical constriction and display an abnormal apical myosin pattern. Together, these results demonstrate that a contractile actomyosin network across the apical cell surface is organized to drive apical constriction in delaminating neuroblasts.},
langid = {english},
file = {/home/guillaume/Zotero/storage/AGA5N4XH/2153.html}
}
@article{andreevPracticalGuideStorage2020,
title = {Practical {{Guide}} to {{Storage}} of {{Large Amounts}} of {{Microscopy Data}}},
author = {Andreev, Andrey and Koo, Daniel E. S.},
date = {2020-07},
journaltitle = {Microscopy Today},
volume = {28},
number = {4},
pages = {42--45},
publisher = {{Cambridge University Press}},
issn = {1551-9295, 2150-3583},
doi = {10.1017/S1551929520001091},
url = {https://www.cambridge.org/core/journals/microscopy-today/article/practical-guide-to-storage-of-large-amounts-of-microscopy-data/D3CE39447BFF5BBF9B3ED8A0C35C6F36},
urldate = {2020-07-29},
abstract = {, Biological imaging tools continue to increase in speed, scale, and resolution, often resulting in the collection of gigabytes or even terabytes of data in a single experiment. In comparison, the ability of research laboratories to store and manage this data is lagging greatly. This leads to limits on the collection of valuable data and slows data analysis and research progress. Here we review common ways researchers store data and outline the drawbacks and benefits of each method. We also offer a blueprint and budget estimation for a currently deployed data server used to store large datasets from zebrafish brain activity experiments using light-sheet microscopy. Data storage strategy should be carefully considered and different options compared when designing imaging experiments.},
langid = {english},
keywords = {big data,data management infrastructure,data workflow,light-sheet microscopy,zebrafish brains},
file = {/home/guillaume/Zotero/storage/4G4DQA6Q/Andreev et Koo - 2020 - Practical Guide to Storage of Large Amounts of Mic.pdf;/home/guillaume/Zotero/storage/PZMIUU8S/D3CE39447BFF5BBF9B3ED8A0C35C6F36.html}
}
@article{atiaGeometricConstraintsEpithelial2018,
title = {Geometric Constraints during Epithelial Jamming},
author = {Atia, Lior and Bi, Dapeng and Sharma, Yasha and Mitchel, Jennifer A. and Gweon, Bomi and A. Koehler, Stephan and DeCamp, Stephen J. and Lan, Bo and Kim, Jae Hun and Hirsch, Rebecca and Pegoraro, Adrian F. and Lee, Kyu Ha and Starr, Jacqueline R. and Weitz, David A. and Martin, Adam C. and Park, Jin-Ah and Butler, James P. and Fredberg, Jeffrey J.},
date = {2018-04-02},
journaltitle = {Nature Physics},
pages = {1},
issn = {1745-2481},
doi = {10.1038/s41567-018-0089-9},
url = {https://www.nature.com/articles/s41567-018-0089-9},
urldate = {2018-04-05},
abstract = {Epithelial cells are shown to scale via a shape distribution that is common to a number of different systems, suggesting that cell shape and shape variability are constrained through a relationship that is purely geometrical.},
langid = {english},
file = {/home/guillaume/Zotero/storage/NEFCQ5US/s41567-018-0089-9.html}
}
@article{baillesGeneticInductionMechanochemical2019,
title = {Genetic Induction and Mechanochemical Propagation of a Morphogenetic Wave},
author = {Bailles, Anaïs and Collinet, Claudio and Philippe, Jean-Marc and Lenne, Pierre-François and Munro, Edwin and Lecuit, Thomas},
date = {2019-08-14},
journaltitle = {Nature},
pages = {1--7},
issn = {1476-4687},
doi = {10.1038/s41586-019-1492-9},
url = {https://www.nature.com/articles/s41586-019-1492-9},
urldate = {2019-08-19},
abstract = {Tissue shape changes in the posterior endoderm of the\ early Drosophila embryo are driven by actomyosin contractions emerging from a transcriptional induction followed by a mechanically-driven propagation of RhoI–myosin II activation.},
langid = {english},
file = {/home/guillaume/Zotero/storage/EUQ4CIWG/s41586-019-1492-9.html}
}
@article{bambardekar_direct_2014,
title = {Direct Laser Manipulation Reveals the Mechanics of Cell Contacts in Vivo},
author = {Bambardekar, Kapil and Clément, Raphaël and Blanc, Olivier and Chardès, Claire and Lenne, Pierre-françois},
date = {2014},
volume = {112},
number = {5},
pages = {1416--1421},
doi = {10.1073/pnas.1418732112},
file = {/home/guillaume/Zotero/storage/IX2N552I/Bambardekar et al. - 2014 - Direct laser manipulation reveals the mechanics of cell contacts in vivo.pdf}
}
@article{bartonActiveVertexModel2016,
title = {Active {{Vertex Model}} for {{Cell}}-{{Resolution Description}} of {{Epithelial Tissue Mechanics}}},
author = {Barton, Daniel L. and Henkes, Silke and Weijer, Cornelis J. and Sknepnek, Rastko},
date = {2016-12-18},
journaltitle = {bioRxiv},
pages = {095133},
doi = {10.1101/095133},
url = {http://biorxiv.org/content/early/2016/12/18/095133},
urldate = {2016-12-20},
abstract = {We introduce an Active Vertex Model (AVM) for cell-resolution studies of the mechanics of confluent epithelial tissues consisting of tens of thousands of cells, with a level of detail inaccessible to similar methods. The AVM combines the Vertex Model for confluent epithelial tissues with active matter dynamics. This introduces a natural description of the cell motion and accounts for motion patterns observed on multiple scales. Furthermore, cell contacts are generated dynamically from positions of cell centres. This not only enables efficient numerical implementation, but provides a natural description of the T1 transition events responsible for local tissue rearrangements. The AVM also includes cell alignment, cell-specific mechanical properties, cell growth, division and apoptosis. In addition, the AVM introduces a flexible, dynamically changing boundary of the epithelial sheet allowing for studies of phenomena such as the fingering instability or wound healing. We illustrate these capabilities with a number of case studies.},
langid = {english},
file = {/home/guillaume/Zotero/storage/BZIXCB9F/Barton et al. - 2016 - Active Vertex Model for Cell-Resolution Descriptio.pdf;/home/guillaume/Zotero/storage/84KDUWF9/095133.html}
}
@article{belmonteVirtualtissueComputerSimulations2016,
title = {Virtual-Tissue Computer Simulations Define the Roles of Cell Adhesion and Proliferation in the Onset of Kidney Cystic Disease},
author = {Belmonte, Julio M. and Clendenon, Sherry G. and Oliveira, Guilherme M. and Swat, Maciej H. and Greene, Evan V. and Jeyaraman, Srividhya and Glazier, James A. and Bacallao, Robert L.},
date = {2016-05-18},
journaltitle = {MBoC},
volume = {27},
number = {22},
pages = {3673--3685},
publisher = {{American Society for Cell Biology (mboc)}},
issn = {1059-1524},
doi = {10.1091/mbc.E16-01-0059},
url = {https://www.molbiolcell.org/doi/full/10.1091/mbc.E16-01-0059},
urldate = {2021-01-29},
abstract = {In autosomal dominant polycystic kidney disease (ADPKD), cysts accumulate and progressively impair renal function. Mutations in PKD1 and PKD2 genes are causally linked to ADPKD, but how these mutations drive cell behaviors that underlie ADPKD pathogenesis is unknown. Human ADPKD cysts frequently express cadherin-8 (cad8), and expression of cad8 ectopically in vitro suffices to initiate cystogenesis. To explore cell behavioral mechanisms of cad8-driven cyst initiation, we developed a virtual-tissue computer model. Our simulations predicted that either reduced cell–cell adhesion or reduced contact inhibition of proliferation triggers cyst induction. To reproduce the full range of cyst morphologies observed in vivo, changes in both cell adhesion and proliferation are required. However, only loss-of-adhesion simulations produced morphologies matching in vitro cad8-induced cysts. Conversely, the saccular cysts described by others arise predominantly by decreased contact inhibition, that is, increased proliferation. In vitro experiments confirmed that cell–cell adhesion was reduced and proliferation was increased by ectopic cad8 expression. We conclude that adhesion loss due to cadherin type switching in ADPKD suffices to drive cystogenesis. Thus, control of cadherin type switching provides a new target for therapeutic intervention.},
file = {/home/guillaume/Zotero/storage/CFLMGGB9/Belmonte et al. - 2016 - Virtual-tissue computer simulations define the rol.pdf;/home/guillaume/Zotero/storage/GVT262R7/mbc.html}
}
@article{benazerafMultiscaleQuantificationTissue2017,
title = {Multiscale Quantification of Tissue Behavior during Amniote Embryo Axis Elongation},
author = {Benazeraf, Bertrand and Beaupeux, Mathias and Tchernookov, Martin and Wallingford, Allison and Salisbury, Tasha and Shirtz, Amelia and Shirtz, Andrew and Huss, Dave and Pourquie, Olivier and Francois, Paul and Lansford, Rusty},
date = {2017-02-10},
journaltitle = {bioRxiv},
pages = {053124},
doi = {10.1101/053124},
url = {http://biorxiv.org/content/early/2017/02/10/053124},
urldate = {2017-03-08},
abstract = {Embryonic axis extension is a complex multi-tissue morphogenetic process responsible for the formation of the posterior part of the amniote body. Cells located in the caudal part of the embryo divide and rearrange to participate in the elongation of the different embryonic tissues (e.g. neural tube, axial and paraxial mesoderm, lateral plate, ectoderm, endoderm). We previously identified the paraxial mesoderm as a crucial player of axis elongation, but how movements and growth are coordinated between the different posterior tissues to drive morphogenesis remain largely unknown. Here we use the quail embryo as a model system to quantify cell behavior and movements in the various tissues of the elongating embryo. We first quantify the tissue-specific contribution to axis elongation by using 3D volumetric techniques, then quantify tissue-specific parameters such as cell density and proliferation at different embryonic stages. To be able to study cell behavior at a multi-tissue scale we used high-resolution 4D imaging of transgenic quail embryos expressing constitutively expressed fluorescent proteins. We developed specific tracking and image analysis techniques to analyze cell motion and compute tissue deformations in 4D. This analysis reveals extensive sliding between tissues during axis extension. Further quantification of tissue tectonics showed patterns of rotations, contractions and expansions, which are coherent with the multi-tissue behavior observed previously. Our results confirm the central role of the PSM in axis extension; we propose that the PSM specific cell proliferation and migration programs control the coordination of elongation between tissues during axis extension.},
langid = {english},
file = {/home/guillaume/Zotero/storage/92HXK7IJ/Benazeraf et al. - 2017 - Multiscale quantification of tissue behavior durin.pdf;/home/guillaume/Zotero/storage/STSZTEPX/053124.html}
}
@article{bergstralh_lateral_2015,
title = {Lateral Adhesion Drives Reintegration of Misplaced Cells into Epithelial Monolayers.},
author = {Bergstralh, Dan T and Lovegrove, Holly E and St Johnston, Daniel},
date = {2015-09},
journaltitle = {Nature cell biology},
volume = {17},
number = {11},
eprint = {26414404},
eprinttype = {pmid},
pages = {1497--1503},
issn = {1476-4679},
doi = {10.1038/ncb3248},
url = {http://www.nature.com.gate1.inist.fr/ncb/journal/v17/n11/full/ncb3248.html#affil-auth},
abstract = {Cells in simple epithelia orient their mitotic spindles in the plane of the epithelium so that both daughter cells are born within the epithelial sheet. This is assumed to be important to maintain epithelial integrity and prevent hyperplasia, because misaligned divisions give rise to cells outside the epithelium. Here we test this assumption in three types of Drosophila epithelium; the cuboidal follicle epithelium, the columnar early embryonic ectoderm, and the pseudostratified neuroepithelium. Ectopic expression of Inscuteable in these tissues reorients mitotic spindles, resulting in one daughter cell being born outside the epithelial layer. Live imaging reveals that these misplaced cells reintegrate into the tissue. Reducing the levels of the lateral homophilic adhesion molecules Neuroglian or Fasciclin 2 disrupts reintegration, giving rise to extra-epithelial cells, whereas disruption of adherens junctions has no effect. Thus, the reinsertion of misplaced cells seems to be driven by lateral adhesion, which pulls cells born outside the epithelial layer back into it. Our findings reveal a robust mechanism that protects epithelia against the consequences of misoriented divisions.},
langid = {english}
}
@article{biDensityindependentRigidityTransition2015,
title = {A Density-Independent Rigidity Transition in Biological Tissues},
author = {Bi, Dapeng and Lopez, J. H. and Schwarz, J. M. and Manning, M. Lisa},
date = {2015-09-21},
journaltitle = {Nature Physics},
volume = {11},
pages = {1074},
url = {https://doi.org/10.1038/nphys3471}
}
@article{bielmeier_interface_2016,
title = {Interface {{Contractility}} between {{Differently Fated Cells Drives Cell Elimination}} and {{Cyst Formation}}},
author = {Bielmeier, Christina and Alt, Silvanus and Vanessa, Weichselberger and La Fortezza, Marco and Harz, Hartmann and Jülicher, Frank and Salbreux, Guillaume and Classen, Ann-Kathrin},
date = {2016},
journaltitle = {Current Biology},
volume = {26},
pages = {563--574},
doi = {10.1016/j.cub.2015.12.063},
keywords = {actomyosin contractility,apoptosis,cell elimination,continuum mechanics,epithelial cyst,epithelium,physical modeling,tissue patterning,vertex model},
file = {/home/guillaume/Zotero/storage/V9C8QWU8/Bielmeier et al. - 2016 - Interface Contractility between Differently Fated Cells Drives Cell Elimination and Cyst Formation.pdf}
}
@article{blanchard_tissue_2009,
title = {Tissue Tectonics: Morphogenetic Strain Rates, Cell Shape Change and Intercalation.},
author = {Blanchard, Guy B and Kabla, Alexandre J and Schultz, Nora L and Butler, Lucy C and Sanson, Benedicte and Gorfinkiel, Nicole and Mahadevan, L and Adams, Richard J},
date = {2009},
journaltitle = {Nature methods},
volume = {6},
number = {6},
eprint = {19412170},
eprinttype = {pmid},
pages = {458--464},
issn = {1548-7091},
doi = {10.1038/nmeth.1327},
url = {http://dx.doi.org/10.1038/nmeth.1327},
abstract = {The dynamic reshaping of tissues during morphogenesis results from a combination of individual cell behaviors and collective cell rearrangements. However, a comprehensive framework to unambiguously measure and link cell behavior to tissue morphogenesis is lacking. Here we introduce such a kinematic framework, bridging cell and tissue behaviors at an intermediate, mesoscopic, level of cell clusters or domains. By measuring domain deformation in terms of the relative motion of cell positions and the evolution of their shapes, we characterized the basic invariant quantities that measure fundamental classes of cell behavior, namely tensorial rates of cell shape change and cell intercalation. In doing so we introduce an explicit definition of cell intercalation as a continuous process. We mapped strain rates spatiotemporally in three models of tissue morphogenesis, gaining insight into morphogenetic mechanisms. Our quantitative approach has broad relevance for the precise characterization and comparison of morphogenetic phenotypes.},
file = {/home/guillaume/Zotero/storage/MN4SXG7V/Blanchard et al. - 2009 - Tissue tectonics morphogenetic strain rates, cell shape change and intercalation.pdf}
}
@article{blanchardPulsatileApicomedialContractility2018,
title = {From Pulsatile Apicomedial Contractility to Effective Epithelial Mechanics},
author = {Blanchard, Guy B and Étienne, Jocelyn and Gorfinkiel, Nicole},
date = {2018-08-01},
journaltitle = {Current Opinion in Genetics \& Development},
series = {Developmental Mechanisms, Patterning and Evolution},
volume = {51},
pages = {78--87},
issn = {0959-437X},
doi = {10.1016/j.gde.2018.07.004},
url = {http://www.sciencedirect.com/science/article/pii/S0959437X18300108},
urldate = {2018-08-01},
abstract = {We review recent developments in the understanding of the biomechanics of apicomedial actomyosin and how its contractility can tense and deform tissue. Myosin pulses are driven by a biochemical oscillator but how they are modulated by the mechanical context remains unclear. On the other hand, the emergence of tissue behaviour is highly dependent on the material properties of actin, on how strongly components are connected and on the influence of neighbouring tissues. We further review the use of constitutive equations in exploring the mechanics of epithelial apices dominated by apicomedial Myosin contractility.},
file = {/home/guillaume/Zotero/storage/UKTF49SK/Blanchard et al. - 2018 - From pulsatile apicomedial contractility to effect.pdf;/home/guillaume/Zotero/storage/XA28RNIE/S0959437X18300108.html}
}
@article{blanchardTakingStrainQuantifying2017,
title = {Taking the Strain: Quantifying the Contributions of All Cell Behaviours to Changes in Epithelial Shape},
shorttitle = {Taking the Strain},
author = {Blanchard, Guy B.},
date = {2017-05-19},
journaltitle = {Phil. Trans. R. Soc. B},
volume = {372},
number = {1720},
eprint = {28348250},
eprinttype = {pmid},
pages = {20150513},
issn = {0962-8436, 1471-2970},
doi = {10.1098/rstb.2015.0513},
url = {http://rstb.royalsocietypublishing.org/content/372/1720/20150513},
urldate = {2017-04-04},
abstract = {Computer-assisted tracking of the shapes of many cells over long periods of development has driven the exploration of novel ways to quantify the contributions of different cell behaviours to morphogenesis. A handful of similar methods have now been published that are used to calculate tissue deformations (strain rates) in epithelia. These methods are further used to quantify strain rates attributable to each of the cell behaviours in the tissue, such as cell shape change, cell rearrangement and cell division, that together sum to the tissue strain rates. In this review, aimed at developmental biologists, I will introduce the general approach, characterize differences in current approaches and highlight extensions of these methods that remain to be fully explored. The methods will make a major contribution to the emerging field of tissue mechanics. Precisely quantified strain rates are an essential first step towards exploring constitutive equations relating stress to strain via tissue mechanical properties. This article is part of the themed issue ‘Systems morphodynamics: understanding the development of tissue hardware’.},
langid = {english},
file = {/home/guillaume/Zotero/storage/2SRHQUUP/20150513.html}
}
@article{bonfantiUnifiedRheologicalModel2019,
title = {A Unified Rheological Model for Cells and Cellularised Materials},
author = {Bonfanti, Alessandra and Fouchard, Jonathan and Khalilgharibi, Nargess and Charras, Guillaume and Kabla, Alexandre},
date = {2019-02-08},
journaltitle = {bioRxiv},
pages = {543330},
doi = {10.1101/543330},
url = {https://www.biorxiv.org/content/10.1101/543330v1},
urldate = {2019-02-13},
abstract = {{$<$}p{$>$}The mechanical response of single cells and tissues exhibits a broad distribution of time scales that gives often rise to a distinctive power-law regime. Such complex behaviour cannot be easily captured by traditional rheological approaches, making material characterisation and predictive modelling very challenging. Here, we present a novel model combining conventional viscoelastic elements with fractional calculus that successfully captures the macroscopic relaxation response of epithelial monolayers. The parameters extracted from the fitting of the relaxation modulus allow prediction of the response of the same material to slow stretch and creep, indicating that the model captured intrinsic material properties. Two characteristic times can be derived from the model parameters, and together these explain different qualitative behaviours observed in creep after genetic and chemical treatments. We compared the response of tissues with the behaviour of single cells as well as intra-cellular and extra-cellular components, and linked the power-law behaviour of the epithelium to the dynamics of the cell cortex. Such a unified model for the mechanical response of biological materials provides a novel and robust mathematical approach for diagnostic methods based on mechanical traits as well as more accurate computational models of tissues mechanics.{$<$}/p{$>$}},
langid = {english},
file = {/home/guillaume/Zotero/storage/SSYETMEB/543330v1.html}
}
@article{bosveld_epithelial_2016,
title = {Epithelial Tricellular Junctions Act as Interphase Cell Shape Sensors to Orient Mitosis},
author = {Bosveld, Floris and Markova, Olga and Guirao, Boris and Martin, Charlotte and Wang, Zhimin and Pierre, Anaëlle and Balakireva, Maria and Gaugue, Isabelle and Ainslie, Anna and Christophorou, Nicolas and Lubensky, David K. and Minc, Nicolas and Bellaïche, Yohanns},
date = {2016-02},
journaltitle = {Nature},
issn = {0028-0836},
doi = {10.1038/nature16970},
url = {http://www.nature.com/nature/journal/vaop/ncurrent/full/nature16970.html?WT.ec_id=NATURE-20160218&spMailingID=50720412&spUserID=MjA1Nzc0NzA0NAS2&spJobID=862152809&spReportId=ODYyMTUyODA5S0},
langid = {english}
}
@article{brezavscekModelEpithelialInvagination2012,
title = {A {{Model}} of {{Epithelial Invagination Driven}} by {{Collective Mechanics}} of {{Identical Cells}}},
author = {Brezavšček, Ana Hočevar and Rauzi, Matteo and Leptin, Maria and Ziherl, Primož},
date = {2012-09-05},
journaltitle = {Biophysical Journal},
volume = {103},
number = {5},
eprint = {23009857},
eprinttype = {pmid},
pages = {1069--1077},
issn = {0006-3495},
doi = {10.1016/j.bpj.2012.07.018},
url = {http://www.cell.com/biophysj/abstract/S0006-3495(12)00793-X},
urldate = {2018-03-12},
abstract = {We propose a 2D mechanical model of a tubular epithelium resembling the early Drosophila embryo. The model consists of a single layer of identical cells with energy associated with the tension of cell cortex. Depending on the relative tension of the apical, basal, and lateral sides of the cells, tissue thickness, and the degree of external constraint, the minimal-energy states of the epithelial cross section include circular shapes as well as a range of inward-buckled shapes. Some of the solutions are characterized by a single deep groove, which shows that an epithelium consisting of cells of identical mechanical properties can infold. This is consistent with what is seen in embryos of certain Drosophila mutants. To ensure that the infolding occurs at a predetermined section of the epithelium, we extend the model by increasing the cross-sectional area of a subset of cells, which is consistent with observations in wild-type embryos. This variation of cell parameters across the epithelium is sufficient to make it fold at a specific site. The model explores previously untested minimal conditions for tissue invagination and is devoid of specificity needed to accurately describe an in~vivo situation in Drosophila.},
langid = {english},
file = {/home/guillaume/Zotero/storage/5V8W2TEL/Brezavšček et al. - 2012 - A Model of Epithelial Invagination Driven by Colle.pdf;/home/guillaume/Zotero/storage/G4CDNLFB/S0006-3495(12)00793-X.html}
}
@online{Build246DamCB,
title = {Build \#246 - {{DamCB}}/Tyssue - {{Travis CI}}},
url = {https://travis-ci.org/DamCB/tyssue/builds/201100834},
urldate = {2017-02-13},
file = {/home/guillaume/Zotero/storage/PS785R2Q/201100834.html}
}
@article{carterPavementCellsTopology2017,
title = {Pavement Cells and the Topology Puzzle},
author = {Carter, Ross and Sanchez-Corrales, Yara Elena and Grieneisen, Veronica A. and Maree, Athanasius F. M.},
date = {2017-07-07},
journaltitle = {bioRxiv},
pages = {160762},
doi = {10.1101/160762},
url = {http://www.biorxiv.org/content/early/2017/07/07/160762},
urldate = {2017-07-10},
abstract = {{$<$}p{$>$}D9Arcy Thompson emphasised the importance of surface tension as a potential driving force in establishing cell shape and topology within tissues. Leaf epidermal pavement cells grow into jigsaw-piece shapes, highly deviating from such classical forms. We investigate the topology of developing Arabidopsis leaves composed solely of pavement cells. Image analysis of around 50,000 cells reveals a clear and unique topological signature, deviating from previously studied epidermal tissues. This topological distribution is however established early during leaf development, already before the typical pavement cell shapes emerge, with topological homeostasis maintained throughout growth and unaltered between division and maturation zones. Simulating graph models, we identify a heuristic cellular division rule that reproduces the observed topology. Our parsimonious model predicts how and when cells effectively place their division plane with respect to their neighbours. We verify the predicted dynamics through in vivo tracking of 800 mitotic events, and conclude that the distinct topology is not a direct consequence of the jigsaw-like shape of the cells, but rather owes itself to a strongly life-history-driven process, with limited impact from cell surface mechanics.{$<$}/p{$>$}},
langid = {english},
file = {/home/guillaume/Zotero/storage/F3FABDJW/Carter et al. - 2017 - Pavement cells and the topology puzzle.pdf;/home/guillaume/Zotero/storage/JPMVQN9R/160762.full.html}
}
@online{centerforhistoryandnewmediaGuideRapidePour,
title = {Guide Rapide Pour Débuter},
author = {{Center for History and New Media}},
url = {http://zotero.org/support/quick_start_guide}
}
@article{chanPatternedCorticalTension2017,
title = {Patterned Cortical Tension Mediated by {{N}}-Cadherin Controls Cell Geometric Order in the {{Drosophila}} Eye},
author = {Chan, Eunice HoYee and Shivakumar, Pruthvi Chavadimane and Clément, Raphaël and Laugier, Edith and Lenne, Pierre-François},
date = {2017-05-24},
journaltitle = {eLife},
volume = {6},
pages = {e22796},
issn = {2050-084X},
doi = {10.7554/eLife.22796},
url = {https://elifesciences.org/content/6/e22796v1},
urldate = {2017-05-26},
abstract = {N-cadherin at heterotypic contacts controls the level and asymmetric localisation of Myosin-II motor, thereby influencing cell shapes and cell packing.},
langid = {english},
keywords = {<italic>D. melanogaster</italic>,cell adhesion,cell contractility,cell mechanics,cell shapes,modelling,Morphogenesis},
file = {/home/guillaume/Zotero/storage/RQZCM29J/Chan et al. - 2017 - Patterned cortical tension mediated by N-cadherin .pdf;/home/guillaume/Zotero/storage/KEF75PC5/e22796.html}
}
@article{chaouiyaSBMLQualitativeModels2013,
title = {{{SBML}} Qualitative Models: A Model Representation Format and Infrastructure to Foster Interactions between Qualitative Modelling Formalisms and Tools},
shorttitle = {{{SBML}} Qualitative Models},
author = {Chaouiya, Claudine and Bérenguier, Duncan and Keating, Sarah M. and Naldi, Aurélien and van Iersel, Martijn P. and Rodriguez, Nicolas and Dräger, Andreas and Büchel, Finja and Cokelaer, Thomas and Kowal, Bryan and Wicks, Benjamin and Gonçalves, Emanuel and Dorier, Julien and Page, Michel and Monteiro, Pedro T. and von Kamp, Axel and Xenarios, Ioannis and de Jong, Hidde and Hucka, Michael and Klamt, Steffen and Thieffry, Denis and Le Novère, Nicolas and Saez-Rodriguez, Julio and Helikar, Tomáš},
options = {useprefix=true},
date = {2013},
journaltitle = {BMC Systems Biology},
volume = {7},
pages = {135},
issn = {1752-0509},
doi = {10.1186/1752-0509-7-135},
url = {http://dx.doi.org/10.1186/1752-0509-7-135},
urldate = {2016-11-02},
abstract = {Qualitative frameworks, especially those based on the logical discrete formalism, are increasingly used to model regulatory and signalling networks. A major advantage of these frameworks is that they do not require precise quantitative data, and that they are well-suited for studies of large networks. While numerous groups have developed specific computational tools that provide original methods to analyse qualitative models, a standard format to exchange qualitative models has been missing.},
file = {/home/guillaume/Zotero/storage/I6ACIJU5/Chaouiya et al. - 2013 - SBML qualitative models a model representation fo.pdf;/home/guillaume/Zotero/storage/SGSHK45P/1752-0509-7-135.html}
}
@article{cheddadi_mod_2010,
title = {{{Mod}}´ Elisation Num´ Erique d'´ Ecoulements de Mousse},
author = {Cheddadi, Ibrahim},
date = {2010}
}
@article{chenExtracellularMatrixStiffness2019,
title = {Extracellular Matrix Stiffness Cues Junctional Remodeling for {{3D}} Tissue Elongation},
author = {Chen, Dong-Yuan and Crest, Justin and Streichan, Sebastian J. and Bilder, David},
date = {2019-07-26},
journaltitle = {Nat Commun},
volume = {10},
number = {1},
pages = {1--15},
issn = {2041-1723},
doi = {10.1038/s41467-019-10874-x},
url = {https://www.nature.com/articles/s41467-019-10874-x},
urldate = {2019-08-30},
abstract = {The extracellular matrix can shape developing organs, but how external forces direct intercellular morphogenesis is unclear. Here, the authors use 3D imaging to show that elongation of the Drosophila egg chamber involves polarized cell reorientation signalled by changes in stiffness of the surrounding extracellular matrix.},
langid = {english},
file = {/home/guillaume/Zotero/storage/7PIYA6CG/Chen et al. - 2019 - Extracellular matrix stiffness cues junctional rem.pdf;/home/guillaume/Zotero/storage/LPS26KHN/s41467-019-10874-x.html}
}
@article{chenMechanicalForcesCell2018,
title = {Mechanical Forces in Cell Monolayers},
author = {Chen, Tianchi and Saw, Thuan Beng and Mège, René-Marc and Ladoux, Benoit},
date = {2018-12-15},
journaltitle = {J Cell Sci},
volume = {131},
number = {24},
pages = {jcs218156},
issn = {0021-9533, 1477-9137},
doi = {10.1242/jcs.218156},
url = {http://jcs.biologists.org/content/131/24/jcs218156},
urldate = {2018-12-20},
abstract = {Skip to Next Section In various physiological processes, the cell collective is organized in a monolayer, such as seen in a simple epithelium. The advances in the understanding of mechanical behavior of the monolayer and its underlying cellular and molecular mechanisms will help to elucidate the properties of cell collectives. In this Review, we discuss recent in vitro studies on monolayer mechanics and their implications on collective dynamics, regulation of monolayer mechanics by physical confinement and geometrical cues and the effect of tissue mechanics on biological processes, such as cell division and extrusion. In particular, we focus on the active nematic property of cell monolayers and the emerging approach to view biological systems in the light of liquid crystal theory. We also highlight the mechanosensing and mechanotransduction mechanisms at the sub-cellular and molecular level that are mediated by the contractile actomyosin cytoskeleton and cell–cell adhesion proteins, such as E-cadherin and α-catenin. To conclude, we argue that, in order to have a holistic understanding of the cellular response to biophysical environments, interdisciplinary approaches and multiple techniques – from large-scale traction force measurements to molecular force protein sensors – must be employed.},
langid = {english},
file = {/home/guillaume/Zotero/storage/QSQ8XEWU/10.1242@jcs.218156.pdf;/home/guillaume/Zotero/storage/RUJWGBJG/jcs218156.html}
}
@article{christiansenSilicoLabelingPredicting2018,
title = {In {{Silico Labeling}}: {{Predicting Fluorescent Labels}} in {{Unlabeled Images}}},
shorttitle = {In {{Silico Labeling}}},
author = {Christiansen, Eric M. and Yang, Samuel J. and Ando, D. Michael and Javaherian, Ashkan and Skibinski, Gaia and Lipnick, Scott and Mount, Elliot and O’Neil, Alison and Shah, Kevan and Lee, Alicia K. and Goyal, Piyush and Fedus, William and Poplin, Ryan and Esteva, Andre and Berndl, Marc and Rubin, Lee L. and Nelson, Philip and Finkbeiner, Steven},
date = {2018-04-19},
journaltitle = {Cell},
volume = {173},
number = {3},
eprint = {29656897},
eprinttype = {pmid},
pages = {792-803.e19},
issn = {0092-8674, 1097-4172},
doi = {10.1016/j.cell.2018.03.040},
url = {https://www.cell.com/cell/abstract/S0092-8674(18)30364-7},
urldate = {2018-04-26},
abstract = {Microscopy is a central method in life sciences. Many popular methods, such as antibody labeling, are used to add physical fluorescent labels to specific cellular constituents. However, these approaches have significant drawbacks, including inconsistency; limitations in the number of simultaneous labels because of spectral overlap; and necessary perturbations of the experiment, such as fixing the cells, to generate the measurement. Here, we show that a computational machine-learning approach, which we call “in silico labeling” (ISL), reliably predicts some fluorescent labels from transmitted-light images of unlabeled fixed or live biological samples. ISL predicts a range of labels, such as those for nuclei, cell type (e.g., neural), and cell state (e.g., cell death). Because prediction happens in silico, the method is consistent, is not limited by spectral overlap, and does not disturb the experiment. ISL generates biological measurements that would otherwise be problematic or impossible to acquire.},
langid = {english},
keywords = {cancer,computer vision,deep learning,machine learning,microscopy,neuroscience,stem cells},
file = {/home/guillaume/Zotero/storage/B994UQ82/S0092-8674(18)30364-7.html;/home/guillaume/Zotero/storage/ZJPN3QXA/S0092-8674(18)30364-7.html}
}
@article{civelekoglu-scholeyModelChromosomeMotility2006,
title = {Model of {{Chromosome Motility}} in {{Drosophila Embryos}}: {{Adaptation}} of a {{General Mechanism}} for {{Rapid Mitosis}}},
shorttitle = {Model of {{Chromosome Motility}} in {{Drosophila Embryos}}},
author = {Civelekoglu-Scholey, G. and Sharp, D. J. and Mogilner, A. and Scholey, J. M.},
date = {2006-06-01},
journaltitle = {Biophysical Journal},
volume = {90},
number = {11},
eprint = {16533843},
eprinttype = {pmid},
pages = {3966--3982},
issn = {0006-3495},
doi = {10.1529/biophysj.105.078691},
url = {https://www.cell.com/biophysj/abstract/S0006-3495(06)72579-6},
urldate = {2019-09-02},
langid = {english},
keywords = {electron microscopy,EM,fluorescence recovery after photobleaching,FRAP,interpolar microtubule,ipMT,kinetochore,kinetochore microtubule,kMT,kt,microtubule,MT},
file = {/home/guillaume/Zotero/storage/B82U2YHW/Civelekoglu-Scholey et al. - 2006 - Model of Chromosome Motility in Drosophila Embryos.pdf;/home/guillaume/Zotero/storage/INBB7I74/S0006-3495(06)72579-6.html}
}
@article{clevers_modeling_2016,
title = {Modeling {{Development}} and {{Disease}} with {{Organoids}}},
author = {Clevers, Hans and Antonica, F. and Kasprzyk, D.F. and Opitz, R. and Iacovino, M. and Liao, X.H. and Dumitrescu, A.M. and Refetoff, S. and Peremans, K. and Manto, M. and Kyba, M. and Costagliola, S. and Barkauskas, C.E. and Cronce, M.J. and Rackley, C.R. and Bowie, E.J. and Keene, D.R. and Stripp, B.R. and Randell, S.H. and Noble, P.W. and Hogan, B.L. and Barker, N. and van Es, J.H. and Kuipers, J. and Kujala, P. and van den Born, M. and Cozijnsen, M. and Haegebarth, A. and Korving, J. and Begthel, H. and Peters, P.J. and Clevers, H. and Barker, N. and Huch, M. and Kujala, P. and van de Wetering, M. and Snippert, H.J. and van Es, J.H. and Sato, T. and Stange, D.E. and Begthel, H. and van den Born, M. and Al, et and Bartfeld, S. and Bayram, T. and van de Wetering, M. and Huch, M. and Begthel, H. and Kujala, P. and Vries, R. and Peters, P.J. and Clevers, H. and Boj, S.F. and Hwang, C.I. and Baker, L.A. and Chio, I.I. and Engle, D.D. and Corbo, V. and Jager, M. and Ponz-Sarvise, M. and Tiriac, H. and Spector, M.S. and Al, et and Camp, J.G. and Badsha, F. and Florio, M. and Kanton, S. and Gerber, T. and Wilsch-Bräuninger, M. and Lewitus, E. and Sykes, A. and Hevers, W. and Lancaster, M. and Al, et and Chen, K.G. and Mallon, B.S. and McKay, R.D. and Robey, P.G. and Cherry, A.B. and Daley, G.Q. and Chua, C.W. and Shibata, M. and Lei, M. and Toivanen, R. and Barlow, L.J. and Bergren, S.K. and Badani, K.K. and McKiernan, J.M. and Benson, M.C. and Hibshoosh, H. and Al, et and Ciancanelli, M.J. and Huang, S.X. and Luthra, P. and Garner, H. and Itan, Y. and Volpi, S. and Lafaille, F.G. and Trouillet, C. and Schmolke, M. and Albrecht, R.A. and Al, et and Clevers, H. and Clevers, H. and Clevers, H. and Loh, K.M. and Nusse, R. and Dekkers, F.e.a. and Dekkers, J.F. and Wiegerinck, C.L. and de Jonge, H.R. and Bronsveld, I. and Janssens, H.M. and Groot, K.M. de Winter-de and Brandsma, A.M. and de Jong, N.W. and Bijvelds, M.J. and Scholte, B.J. and Al, et and Desai, T.J. and Brownfield, D.G. and Krasnow, M.A. and DeWard, A.D. and Cramer, J. and Lagasse, E. and Dorrell, C. and Tarlow, B. and Wang, Y. and Canaday, P.S. and Haft, A. and Schug, J. and Streeter, P.R. and Finegold, M.J. and Shenje, L.T. and Kaestner, K.H. and Grompe, M. and Drost, J. and van Jaarsveld, R.H. and Ponsioen, B. and Zimberlin, C. and van Boxtel, R. and Buijs, A. and Sachs, N. and Overmeer, R.M. and Offerhaus, G.J. and Begthel, H. and Al, et and Dye, B.R. and Hill, D.R. and Ferguson, M.A. and Tsai, Y.H. and Nagy, M.S. and Dyal, R. and Wells, J.M. and Mayhew, C.N. and Nattiv, R. and Klein, O.D. and Al, et and Eiraku, M. and Sasai, Y. and Eiraku, M. and Watanabe, K. and Matsuo-Takasaki, M. and Kawada, M. and Yonemura, S. and Matsumura, M. and Wataya, T. and Nishiyama, A. and Muguruma, K. and Sasai, Y. and Eiraku, M. and Takata, N. and Ishibashi, H. and Kawada, M. and Sakakura, E. and Okuda, S. and Sekiguchi, K. and Adachi, T. and Sasai, Y. and Firth, A.L. and Menon, T. and Parker, G.S. and Qualls, S.J. and Lewis, B.M. and Ke, E. and Dargitz, C.T. and Wright, R. and Khanna, A. and Gage, F.H. and Verma, I.M. and Fordham, R.P. and Yui, S. and Hannan, N.R. and Soendergaard, C. and Madgwick, A. and Schweiger, P.J. and Nielsen, O.H. and Vallier, L. and Pedersen, R.A. and Nakamura, T. and Al, et and Fukuda, M. and Mizutani, T. and Mochizuki, W. and Matsumoto, T. and Nozaki, K. and Sakamaki, Y. and Ichinose, S. and Okada, Y. and Tanaka, T. and Watanabe, M. and Nakamura, T. and Gallico, G.G. and O'Connor, N.E. and Compton, C.C. and Kehinde, O. and Green, H. and Gao, D. and Vela, I. and Sboner, A. and Iaquinta, P.J. and Karthaus, W.R. and Gopalan, A. and Dowling, C. and Wanjala, J.N. and Undvall, E.A. and Arora, V.K. and Al, et and Grün, D. and Lyubimova, A. and Kester, L. and Wiebrands, K. and Basak, O. and Sasaki, N. and Clevers, H. and van Oudenaarden, A. and Huang, S.X. and Islam, M.N. and O'Neill, J. and Hu, Z. and Yang, Y.G. and Chen, Y.W. and Mumau, M. and Green, M.D. and Vunjak-Novakovic, G. and Bhattacharya, J. and Snoeck, H.W. and Huang, L. and Holtzinger, A. and Jagan, I. and BeGora, M. and Lohse, I. and Ngai, N. and Nostro, C. and Wang, R. and Muthuswamy, L.B. and Crawford, H.C. and Al, et and Huch, M. and Bonfanti, P. and Boj, S.F. and Sato, T. and Loomans, C.J. and van de Wetering, M. and Sojoodi, M. and Li, V.S. and Schuijers, J. and Gracanin, A. and Al, et and Huch, M. and Dorrell, C. and Boj, S.F. and van Es, J.H. and Li, V.S. and van de Wetering, M. and Sato, T. and Hamer, K. and Sasaki, N. and Finegold, M.J. and Al, et and Huch, M. and Gehart, H. and van Boxtel, R. and Hamer, K. and Blokzijl, F. and Verstegen, M.M. and Ellis, E. and van Wenum, M. and Fuchs, S.A. and de Ligt, J. and Al, et and Jain, R. and Barkauskas, C.E. and Takeda, N. and Bowie, E.J. and Aghajanian, H. and Wang, Q. and Padmanabhan, A. and Manderfield, L.J. and Gupta, M. and Li, D. and Al, et and Jung, P. and Sato, T. and Merlos-Suárez, A. and Barriga, F.M. and Iglesias, M. and Rossell, D. and Auer, H. and Gallardo, M. and Blasco, M.A. and Sancho, E. and Al, et and Karthaus, W.R. and Iaquinta, P.J. and Drost, J. and Gracanin, A. and van Boxtel, R. and Wongvipat, J. and Dowling, C.M. and Gao, D. and Begthel, H. and Sachs, N. and Al, et and Kessler, M. and Hoffmann, K. and Brinkmann, V. and Thieck, O. and Jackisch, S. and Toelle, B. and Berger, H. and Mollenkopf, H.J. and Mangler, M. and Sehouli, J. and Al, et and Korinek, V. and Barker, N. and Moerer, P. and van Donselaar, E. and Huls, G. and Peters, P.J. and Clevers, H. and Kurmann, A.A. and Serra, M. and Hawkins, F. and Rankin, S.A. and Mori, M. and Astapova, I. and Ullas, S. and Lin, S. and Bilodeau, M. and Rossant, J. and Al, et and Lancaster, M.A. and Knoblich, J.A. and Lancaster, M.A. and Renner, M. and Martin, C.A. and Wenzel, D. and Bicknell, L.S. and Hurles, M.E. and Homfray, T. and Penninger, J.M. and Jackson, A.P. and Knoblich, J.A. and Li, X. and Nadauld, L. and Ootani, A. and Corney, D.C. and Pai, R.K. and Gevaert, O. and Cantrell, M.A. and Rack, P.G. and Neal, J.T. and Chan, C.W. and Al, et and Lindberg, K. and Brown, M.E. and Chaves, H.V. and Kenyon, K.R. and Rheinwald, J.G. and Linnemann, J.R. and Miura, H. and Meixner, L.K. and Irmler, M. and Kloos, U.J. and Hirschi, B. and Bartsch, H.S. and Sass, S. and Beckers, J. and Theis, F.J. and Al, et and Longmire, T.A. and Ikonomou, L. and Hawkins, F. and Christodoulou, C. and Cao, Y. and Jean, J.C. and Kwok, L.W. and Mou, H. and Rajagopal, J. and Shen, S.S. and Al, et and Ma, R. and Latif, R. and Davies, T.F. and Mae, S. and Shono, A. and Shiota, F. and Yasuno, T. and Kajiwara, M. and Gotoda-Nishimura, N. and Arai, S. and Sato-Otubo, A. and Toyoda, T. and Takahashi, K. and Al, et and Maimets, M. and Rocchi, C. and Bron, R. and Pringle, S. and Kuipers, J. and Giepmans, B.N.G. and Vries, R.G.J. and Clevers, H. and Haan, G. De and Os, R. Van and Al, et and Matano, M. and Date, S. and Shimokawa, M. and Takano, A. and Fujii, M. and Ohta, Y. and Watanabe, T. and Kanai, T. and Sato, T. and McCracken, K.W. and Catá, E.M. and Crawford, C.M. and Sinagoga, K.L. and Schumacher, M. and Rockich, B.E. and Tsai, Y.H. and Mayhew, C.N. and Spence, J.R. and Zavros, Y. and Wells, J.M. and Muguruma, K. and Nishiyama, A. and Ono, Y. and Miyawaki, H. and Mizuhara, E. and Hori, S. and Kakizuka, A. and Obata, K. and Yanagawa, Y. and Hirano, T. and Sasai, Y. and Muguruma, K. and Nishiyama, A. and Kawakami, H. and Hashimoto, K. and Sasai, Y. and Nadauld, L.D. and Garcia, S. and Natsoulis, G. and Bell, J.M. and Miotke, L. and Hopmans, E.S. and Xu, H. and Pai, R.K. and Palm, C. and Regan, J.F. and Al, et and Nakano, T. and Ando, S. and Takata, N. and Kawada, M. and Muguruma, K. and Sekiguchi, K. and Saito, K. and Yonemura, S. and Eiraku, M. and Sasai, Y. and Nanduri, L.S. and Baanstra, M. and Faber, H. and Rocchi, C. and Zwart, E. and de Haan, G. and van Os, R. and Coppes, R.P. and Nantasanti, S. and Spee, B. and Kruitwagen, H.S. and Chen, C. and Geijsen, N. and Oosterhoff, L.A. and van Wolferen, M.E. and Pelaez, N. and Fieten, H. and Wubbolts, R.W. and Al, et and O'connor, N.E. and Mulliken, J.B. and Banks-Schlegel, S. and Kehinde, O. and Green, H. and Ootani, A. and Li, X. and Sangiorgi, E. and Ho, Q.T. and Ueno, H. and Toda, S. and Sugihara, H. and Fujimoto, K. and Weissman, I.L. and Capecchi, M.R. and Kuo, C.J. and Pellegrini, G. and Traverso, C.E. and Franzi, A.T. and Zingirian, M. and Cancedda, R. and Luca, M. De and Plaks, V. and Brenot, A. and Lawson, D.A. and Linnemann, J.R. and Kappel, E.C. Van and Wong, K.C. and de Sauvage, F. and Klein, O.D. and Werb, Z. and Qian, X. and Nguyen, H.N. and Song, M.M. and Hadiono, C. and Ogden, S.C. and Hammack, C. and Yao, B. and Hamersky, G.R. and Jacob, F. and Zhong, C. and Al, et and Rama, P. and Matuska, S. and Paganoni, G. and Spinelli, A. and Luca, M. 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options = {useprefix=true},
date = {2016-06},
journaltitle = {Cell},
volume = {165},
number = {7},
pages = {1586--1597},
issn = {00928674},
doi = {10.1016/j.cell.2016.05.082},
url = {http://linkinghub.elsevier.com/retrieve/pii/S0092867416307292}
}
@article{clewleyHybridModelsBiological2012,
title = {Hybrid Models and Biological Model Reduction with {{PyDSTool}}},
author = {Clewley, Robert},
date = {2012},
journaltitle = {PLoS Comput. Biol.},
volume = {8},
number = {8},
eprint = {22912566},
eprinttype = {pmid},
pages = {e1002628},
issn = {1553-7358},
doi = {10.1371/journal.pcbi.1002628},
abstract = {The PyDSTool software environment is designed to develop, simulate, and analyze dynamical systems models, particularly for biological applications. Unlike the engineering application focus and graphical specification environments of most general purpose simulation tools, PyDSTool provides a programmatic environment well suited to exploratory data- and hypothesis-driven biological modeling problems. In this work, we show how the environment facilitates the application of hybrid dynamical modeling to the reverse engineering of complex biophysical dynamics; in this case, of an excitable membrane. The example demonstrates how the software provides novel tools that support the inference and validation of mechanistic hypotheses and the inclusion of data constraints in both quantitative and qualitative ways. The biophysical application is broadly relevant to models in the biosciences. The open source and platform-independent PyDSTool package is freely available under the BSD license from http://sourceforge.net/projects/pydstool/. The hosting service provides links to documentation and online forums for user support.},
langid = {english},
pmcid = {PMC3415397},
keywords = {Biophysics,Models; Biological}
}
@article{coburnContactInhibitionLocomotion2016,
title = {Contact Inhibition of Locomotion and Mechanical Cross-Talk between Cell–Cell and Cell–Substrate Adhesion Determine the Pattern of Junctional Tension in Epithelial Cell Aggregates},
author = {Coburn, Luke and Lopez, Hender and Caldwell, Benjamin J. and Moussa, Elliott and Yap, Chloe and Priya, Rashmi and Noppe, Adrian and Roberts, Anthony P. and Lobaskin, Vladimir and Yap, Alpha S. and Neufeld, Zoltan and Gomez, Guillermo A.},
date = {2016-07-11},
journaltitle = {Mol. Biol. Cell},
volume = {27},
number = {22},
eprint = {27605701},
eprinttype = {pmid},
pages = {3436--3448},
issn = {1059-1524, 1939-4586},
doi = {10.1091/mbc.E16-04-0226},
url = {http://www.molbiolcell.org/content/27/22/3436},
urldate = {2016-11-04},
abstract = {We used a computational approach to analyze the biomechanics of epithelial cell aggregates—islands, stripes, or entire monolayers—that combines both vertex and contact-inhibition-of-locomotion models to include cell–cell and cell–substrate adhesion. Examination of the distribution of cell protrusions (adhesion to the substrate) in the model predicted high-order profiles of cell organization that agree with those previously seen experimentally. Cells acquired an asymmetric distribution of basal protrusions, traction forces, and apical aspect ratios that decreased when moving from the edge to the island center. Our in silico analysis also showed that tension on cell–cell junctions and apical stress is not homogeneous across the island. Instead, these parameters are higher at the island center and scale up with island size, which we confirmed experimentally using laser ablation assays and immunofluorescence. Without formally being a three-dimensional model, our approach has the minimal elements necessary to reproduce the distribution of cellular forces and mechanical cross-talk, as well as the distribution of principal stress in cells within epithelial cell aggregates. By making experimentally testable predictions, our approach can aid in mechanical analysis of epithelial tissues, especially when local changes in cell–cell and/or cell–substrate adhesion drive collective cell behavior.},
langid = {english},
file = {/home/guillaume/Zotero/storage/NWVTPMM2/3436.html}
}
@article{combedazouMyosinIIGoverns2016,
title = {Myosin {{II}} Governs Collective Cell Migration Behaviour Downstream of Guidance Receptor Signalling},
author = {Combedazou, Anne and Choesmel-Cadamuro, Valérie and Gay, Guillaume and Liu, Jiaying and Dupré, Loïc and Ramel, Damien and Wang, Xiaobo},
date = {2016-01-01},
journaltitle = {J Cell Sci},
eprint = {27034137},
eprinttype = {pmid},
pages = {jcs.179952},
issn = {0021-9533, 1477-9137},
doi = {10.1242/jcs.179952},
url = {http://jcs.biologists.org/content/early/2016/03/30/jcs.179952},
urldate = {2017-06-29},
abstract = {Skip to Next Section Border cell migration during Drosophila oogenesis is a potent model to study collective cell migration, a process involved in development and metastasis. Border cell clusters adopt two main types of behaviour during migration: linear and rotational. Still, the molecular mechanism controlling the switch from one to the other is unknown. Here, we demonstrate that non-muscle Myosin II activity controls the linear to rotational switch. Further, we show that the regulation of NMII takes place downstream of guidance receptor signalling and is critical to ensure efficient collective migration. This study thus provides new insight into the molecular mechanism coordinating the different cell behaviours in a migrating cluster.},
langid = {english},
file = {/home/guillaume/Zotero/storage/D6AVGA84/Combedazou et al. - 2016 - Myosin II governs collective cell migration behavi.pdf;/home/guillaume/Zotero/storage/UTDHJNGX/jcs.html}
}
@article{combedazouMyosinIIGoverns2016a,
title = {Myosin {{II}} Governs Collective Cell Migration Behaviour Downstream of Guidance Receptor Signalling},
author = {Combedazou, A and Choesmel-Cadamuro, V and Gay, G and Liu, J and Dupré, L and Ramel, D and Wang, X},
date = {2016-03-31},
journaltitle = {J Cell Sci},
eprint = {27034137},
eprinttype = {pmid},
pages = {jcs.179952},
issn = {0021-9533, 1477-9137},
doi = {10.1242/jcs.179952},
url = {http://jcs.biologists.org/content/early/2016/04/13/jcs.179952},
urldate = {2016-12-11},
abstract = {Skip to Next Section Border cell migration during Drosophila oogenesis is a potent model to study collective cell migration, a process involved in development and metastasis. Border cell clusters adopt two main types of behaviour during migration: linear and rotational. However, the molecular mechanism controlling the switch from one to the other is unknown. Here, we demonstrate that non-muscle Myosin II (NMII, also known as Spaghetti squash) activity controls the linear-to-rotational switch. Furthermore, we show that the regulation of NMII takes place downstream of guidance receptor signalling and is critical to ensure efficient collective migration. This study thus provides new insight into the molecular mechanism coordinating the different cell behaviours in a migrating cluster.},
langid = {english},
file = {/home/guillaume/Zotero/storage/ISDPHQFX/Combedazou et al. - 2016 - Myosin II governs collective cell migration behavi.pdf;/home/guillaume/Zotero/storage/KWZJ8BQP/jcs.html}
}
@online{ComparingIndividualbasedApproaches,
title = {Comparing Individual-Based Approaches to Modelling the Self-Organization of Multicellular Tissues},
url = {https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1005387},
urldate = {2019-09-02},
file = {/home/guillaume/Zotero/storage/EDH2C3GN/article.html}
}
@online{ComputationalFluidDynamics,
title = {Computational Fluid Dynamics with Imaging of Cleared Tissue and of in Vivo Perfusion Predicts Drug Uptake and Treatment Responses in Tumours | {{Nature Biomedical Engineering}}},
url = {https://www.nature.com/articles/s41551-018-0306-y},
urldate = {2018-10-11}
}
@article{conteBiomechanicalAnalysisVentral2012,
title = {A {{Biomechanical Analysis}} of {{Ventral Furrow Formation}} in the {{Drosophila Melanogaster Embryo}}},
author = {Conte, Vito and Ulrich, Florian and Baum, Buzz and Muñoz, Jose and Veldhuis, Jim and Brodland, Wayne and Miodownik, Mark},
date = {2012},
journaltitle = {PLoS ONE},
volume = {7},
number = {4},
eprint = {22511944},
eprinttype = {pmid},
doi = {10.1371/journal.pone.0034473},
url = {/pmcc/articles/PMC3325263/?report=abstract},
urldate = {2018-01-09},
abstract = {PubMed Central Canada (PMC Canada) provides free access to a stable and permanent online digital archive of full-text, peer-reviewed health and life sciences research publications. It builds on PubMed Central (PMC), the U.S. National Institutes of Health (NIH) free digital archive of biomedical and life sciences journal literature and is a member of the broader PMC International (PMCI) network of e-repositories.},
langid = {english},
file = {/home/guillaume/Zotero/storage/7TXKH2NN/PMC3325263.html}
}
@article{conteBiomechanicalAnalysisVentral2012a,
title = {A {{Biomechanical Analysis}} of {{Ventral Furrow Formation}} in the {{Drosophila Melanogaster Embryo}}},
author = {Conte, Vito and Ulrich, Florian and Baum, Buzz and Muñoz, Jose and Veldhuis, Jim and Brodland, Wayne and Miodownik, Mark},
date = {2012-04-12},
journaltitle = {PLOS ONE},
volume = {7},
number = {4},
pages = {e34473},
issn = {1932-6203},
doi = {10.1371/journal.pone.0034473},
url = {http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0034473},
urldate = {2017-03-04},
abstract = {The article provides a biomechanical analysis of ventral furrow formation in the Drosophila melanogaster embryo. Ventral furrow formation is the first large-scale morphogenetic movement in the fly embryo. It involves deformation of a uniform cellular monolayer formed following cellularisation, and has therefore long been used as a simple system in which to explore the role of mechanics in force generation. Here we use a quantitative framework to carry out a systematic perturbation analysis to determine the role of each of the active forces observed. The analysis confirms that ventral furrow invagination arises from a combination of apical constriction and apical–basal shortening forces in the mesoderm, together with a combination of ectodermal forces. We show that the mesodermal forces are crucial for invagination: the loss of apical constriction leads to a loss of the furrow, while the mesodermal radial shortening forces are the primary cause of the internalisation of the future mesoderm as the furrow rises. Ectodermal forces play a minor but significant role in furrow formation: without ectodermal forces the furrow is slower to form, does not close properly and has an aberrant morphology. Nevertheless, despite changes in the active mesodermal and ectodermal forces lead to changes in the timing and extent of furrow, invagination is eventually achieved in most cases, implying that the system is robust to perturbation and therefore over-determined.},
keywords = {Deformation,Drosophila melanogaster,Ectoderm,Embryos,Epithelium,In vivo imaging,Mesoderm,Mesodermal cells},
file = {/home/guillaume/Zotero/storage/P2QUJSCV/Conte et al. - 2012 - A Biomechanical Analysis of Ventral Furrow Formati.pdf;/home/guillaume/Zotero/storage/4GT3W99T/article.html}
}
@article{coravosActomyosinPulsingTissue2017,
title = {Actomyosin {{Pulsing}} in {{Tissue Integrity Maintenance}} during {{Morphogenesis}}},
author = {Coravos, Jonathan S. and Mason, Frank M. and Martin, Adam C.},
date = {2017-04-01},
journaltitle = {Trends in Cell Biology},
volume = {27},
number = {4},
eprint = {27989655},
eprinttype = {pmid},
pages = {276--283},
issn = {0962-8924, 1879-3088},
doi = {10.1016/j.tcb.2016.11.008},
url = {http://www.cell.com/trends/cell-biology/abstract/S0962-8924(16)30206-9},
urldate = {2017-03-24},
langid = {english},
file = {/home/guillaume/Zotero/storage/2BQNNHIP/coravos2016.pdf;/home/guillaume/Zotero/storage/W4TCU87V/S0962-8924(16)30206-9.html}
}
@incollection{cordelieres3DQuantitativeColocalisation2020,
title = {{{3D Quantitative Colocalisation Analysis}}},
booktitle = {Bioimage {{Data Analysis Workflows}}},
author = {Cordelières, Fabrice P. and Zhang, Chong},
editor = {Miura, Kota and Sladoje, Nataša},
date = {2020},
series = {Learning {{Materials}} in {{Biosciences}}},
pages = {33--66},
publisher = {{Springer International Publishing}},
location = {{Cham}},
doi = {10.1007/978-3-030-22386-1_3},
url = {https://doi.org/10.1007/978-3-030-22386-1_3},
urldate = {2019-10-24},
abstract = {In this module we will first build a 3D object based colocalisation macro step by step. Then we will practice to adapt and extend the current macro such that it can also work with intensity-based colocalisation methods.},
isbn = {978-3-030-22386-1},
langid = {english}
}
@article{courtheoux_ase1/prc1-dependent_2009,
title = {Ase1/{{Prc1}}-Dependent Spindle Elongation Corrects Merotely during Anaphase in Fission Yeast},
author = {Courtheoux, T and Gay, G and Gachet, Y and Tournier, S},
date = {2009},
journaltitle = {The Journal of cell biology},
volume = {187},
number = {3},
pages = {399--412}
}
@article{courtheoux_dynein_2007,
title = {Dynein Participates in Chromosome Segregation in Fission Yeast},
author = {Courtheoux, T and Gay, G and Reyes, C and Goldstone, S and Gachet, Y and Tournier, S},
date = {2007},
journaltitle = {Biology of the Cell},
volume = {99},
number = {11},
pages = {627--637}
}
@article{curranMyosinIIControls2017,
title = {Myosin {{II Controls Junction Fluctuations}} to {{Guide Epithelial Tissue Ordering}}},
author = {Curran, Scott and Strandkvist, Charlotte and Bathmann, Jasper and de Gennes, Marc and Kabla, Alexandre and Salbreux, Guillaume and Baum, Buzz},
options = {useprefix=true},
date = {2017-10-26},
journaltitle = {Developmental Cell},
issn = {1534-5807},
doi = {10.1016/j.devcel.2017.09.018},
url = {http://www.sciencedirect.com/science/article/pii/S1534580717307712},
urldate = {2017-11-15},
abstract = {Summary Under conditions of homeostasis, dynamic changes in the length of individual adherens junctions (AJs) provide epithelia with the fluidity required to maintain tissue integrity in the face of intrinsic and extrinsic forces. While the contribution of AJ remodeling to developmental morphogenesis has been intensively studied, less is known about AJ dynamics in other circumstances. Here, we study AJ dynamics in an epithelium that undergoes a gradual increase in packing order, without concomitant large-scale changes in tissue size or shape. We find that neighbor exchange events are driven by stochastic fluctuations in junction length, regulated in part by junctional actomyosin. In this context, the developmental increase of isotropic junctional actomyosin reduces the rate of neighbor exchange, contributing to tissue order. We propose a model in which the local variance in tension between junctions determines whether actomyosin-based forces will inhibit or drive the topological transitions that either refine or deform a tissue.},
keywords = {cadherin,epithelia,junction fluctuations,Morphogenesis,Myosin,neighbor exchange,Tissue mechanics,tissue refinement,vertex model},
file = {/home/guillaume/Zotero/storage/ENNMXRC2/Curran et al. - 2017 - Myosin II Controls Junction Fluctuations to Guide .pdf;/home/guillaume/Zotero/storage/YYMC7LTP/S1534580717307712.html}
}
@article{davidson_emergent_2010,
title = {Emergent Morphogenesis: {{Elastic}} Mechanics of a Self-Deforming Tissue},
author = {a. Davidson, Lance and Joshi, Sagar D. and Kim, Hye Young and von Dassow, Michelangelo and Zhang, Lin and Zhou, Jian},
options = {useprefix=true},
date = {2010},
journaltitle = {Journal of Biomechanics},
volume = {43},
number = {1},
eprint = {19815213},
eprinttype = {pmid},
pages = {63--70},
issn = {00219290},
doi = {10.1016/j.jbiomech.2009.09.010},
url = {http://dx.doi.org/10.1016/j.jbiomech.2009.09.010},
abstract = {Multicellular organisms are generated by coordinated cell movements during morphogenesis. Convergent extension is a key tissue movement that organizes mesoderm, ectoderm, and endoderm in vertebrate embryos. The goals of researchers studying convergent extension, and morphogenesis in general, include understanding the molecular pathways that control cell identity, establish fields of cell types, and regulate cell behaviors. Cell identity, the size and boundaries of tissues, and the behaviors exhibited by those cells shape the developing embryo; however, there is a fundamental gap between understanding the molecular pathways that control processes within single cells and understanding how cells work together to assemble multicellular structures. Theoretical and experimental biomechanics of embryonic tissues are increasingly being used to bridge that gap. The efforts to map molecular pathways and the mechanical processes underlying morphogenesis are crucial to understanding: (1) the source of birth defects, (2) the formation of tumors and progression of cancer, and (3) basic principles of tissue engineering. In this paper, we first review the process of tissue convergent extension of the vertebrate axis and then review models used to study the self-organizing movements from a mechanical perspective. We conclude by presenting a relatively simple "wedge-model" that exhibits key emergent properties of convergent extension such as the coupling between tissue stiffness, cell intercalation forces, and tissue elongation forces. ?? 2009 Elsevier Ltd. All rights reserved.},
keywords = {Cell shape and tissue mechanics,Computer Simulation,Convergence and extension,Convergent extension,Frog,Gastrulation,In silico,Modeling},
file = {/home/guillaume/Zotero/storage/HJKSSG33/Davidson et al. - 2010 - Emergent morphogenesis Elastic mechanics of a self-deforming tissue.pdf}
}
@online{debackStatisticalMathematicalModeling2018,
title = {Statistical and Mathematical Modeling of Spatiotemporal Dynamics of Stem Cells},
author = {de Back, Walter and Zerjatke, Thomas and Roeder, Ingo},
options = {useprefix=true},
date = {2018-09-05},
eprint = {1809.01708},
eprinttype = {arxiv},
primaryclass = {q-bio},
url = {http://arxiv.org/abs/1809.01708},
urldate = {2018-09-13},
abstract = {Statistical and mathematical modeling are crucial to describe, interpret, compare and predict the behavior of complex biological systems including the organization of hematopoietic stem and progenitor cells in the bone marrow environment. The current prominence of high-resolution and live-cell imaging data provides an unprecedented opportunity to study the spatiotemporal dynamics of these cells within their stem cell niche and learn more about aberrant, but also unperturbed, normal hematopoiesis. However, this requires careful quantitative statistical analysis of the spatial and temporal behavior of cells and the interaction with their microenvironment. Moreover, such quantification is a prerequisite for the construction of hypothesis-driven mathematical models that can provide mechanistic explanations by generating spatiotemporal dynamics that can be directly compared to experimental observations. Here, we provide a brief overview of statistical methods in analyzing spatial distribution of cells, cell motility, cell shapes and cellular genealogies. We also describe cell- based modeling formalisms that allow researchers to simulate emergent behavior in a multicellular system based on a set of hypothesized mechanisms. Together, these methods provide a quantitative workflow for the analytic and synthetic study of the spatiotemporal behavior of hematopoietic stem and progenitor cells.},
archiveprefix = {arXiv},
keywords = {Quantitative Biology - Quantitative Methods},
file = {/home/guillaume/Zotero/storage/PNYJNKYB/de Back et al. - 2018 - Statistical and mathematical modeling of spatiotem.pdf;/home/guillaume/Zotero/storage/87PNI822/1809.html}
}
@article{demongeotDiscreteMeshApproach2016,
title = {Discrete {{Mesh Approach}} in {{Morphogenesis Modelling}}: The {{Example}} of {{Gastrulation}}},
shorttitle = {Discrete {{Mesh Approach}} in {{Morphogenesis Modelling}}},
author = {Demongeot, J. and Lontos, A. and Promayon, E.},
date = {2016-12-01},
journaltitle = {Acta Biotheor},
volume = {64},
number = {4},
pages = {427--446},
issn = {0001-5342, 1572-8358},
doi = {10.1007/s10441-016-9301-4},
url = {https://link.springer.com/article/10.1007/s10441-016-9301-4},
urldate = {2017-03-04},
abstract = {Morphogenesis is a general concept in biology including all the processes which generate tissue shapes and cellular organizations in a living organism. Many hybrid formalizations (i.e., with both discrete and continuous parts) have been proposed for modelling morphogenesis in embryonic or adult animals, like gastrulation. We propose first to study the ventral furrow invagination as the initial step of gastrulation, early stage of embryogenesis. We focus on the study of the connection between the apical constriction of the ventral cells and the initiation of the invagination. For that, we have created a 3D biomechanical model of the embryo of the Drosophila melanogaster based on the finite element method. Each cell is modelled by an elastic hexahedron contour and is firmly attached to its neighbouring cells. A uniform initial distribution of elastic and contractile forces is applied to cells along the model. Numerical simulations show that invagination starts at ventral curved extremities of the embryo and then propagates to the ventral medial layer. Then, this observation already made in some experiments can be attributed uniquely to the specific shape of the embryo and we provide mechanical evidence to support it. Results of the simulations of the “pill-shaped” geometry of the Drosophila melanogaster embryo are compared with those of a spherical geometry corresponding to the Xenopus lævis embryo. Eventually, we propose to study the influence of cell proliferation on the end of the process of invagination represented by the closure of the ventral furrow.},
langid = {english},
file = {/home/guillaume/Zotero/storage/BMEZQJRQ/demongeot2016.pdf;/home/guillaume/Zotero/storage/5S7VZWJI/s10441-016-9301-4.html}
}
@article{desclouxParameterfreeImageResolution2019,
title = {Parameter-Free Image Resolution Estimation Based on Decorrelation Analysis},
author = {Descloux, A. and Grußmayer, K. S. and Radenovic, A.},
date = {2019-09},
journaltitle = {Nat Methods},
volume = {16},
number = {9},
pages = {918--924},
publisher = {{Nature Publishing Group}},
issn = {1548-7105},
doi = {10.1038/s41592-019-0515-7},
url = {https://www.nature.com/articles/s41592-019-0515-7},
urldate = {2020-03-25},
abstract = {Decorrelation analysis offers an improved method for assessing image resolution that works on a single image and is insensitive to common image artifacts. The method can be applied generally to any type of microscopy images.},
issue = {9},
langid = {english},
file = {/home/guillaume/Zotero/storage/8KQJIPBC/Descloux et al. - 2019 - Parameter-free image resolution estimation based o.pdf;/home/guillaume/Zotero/storage/LZXIXIAW/s41592-019-0515-7.html}
}
@article{diazdelalozaForcesShapingDrosophila,
title = {Forces Shaping the {{Drosophila}} Wing},
author = {Diaz de la Loza, M. C. and Thompson, B. J.},
journaltitle = {Mechanisms of Development},
issn = {0925-4773},
doi = {10.1016/j.mod.2016.10.003},
url = {http://www.sciencedirect.com/science/article/pii/S0925477316300466},
urldate = {2016-11-03},
abstract = {How genes encode the three-dimensional shape of tissues is a fascinating problem in biology. Pioneering genetic studies in the fruit fly Drosophila have identified key genes that control the generation of force patterns in the developing wing. Shortrange force patterns generated by planar polarised myosins can promote boundary formation and tissue elongation during the larval wing disc stage. Long-range force patterns are also crucial to shaping the wing during the pupal stage. We review the different ways in which both local and global force patterns can be generated, such as: patterned acto-myosin contractility, patterned anchorage to the extracellular matrix, and patterned tissue growth. In all cases, the balance between force, mass, and resistance explains how the resulting mechanical response produces particular tissue forms—a point underscored by the ability of computer simulations of tissue mechanics to reproduce such morphogenetic events.},
file = {/home/guillaume/Zotero/storage/V6V93DVF/Diaz de la Loza et Thompson - Forces shaping the Drosophila wing.pdf;/home/guillaume/Zotero/storage/X3XTTFGG/S0925477316300466.html}
}
@article{drasdoSinglecellbasedModelTumor2005,
title = {A Single-Cell-Based Model of Tumor Growthin Vitro: Monolayers and Spheroids},
shorttitle = {A Single-Cell-Based Model of Tumor Growthin Vitro},
author = {Drasdo, Dirk and Höhme, Stefan},
date = {2005-07},
journaltitle = {Phys. Biol.},
volume = {2},
number = {3},
pages = {133--147},
publisher = {{IOP Publishing}},
issn = {1478-3975},
doi = {10.1088/1478-3975/2/3/001},
url = {https://doi.org/10.1088/1478-3975/2/3/001},
urldate = {2021-02-08},
abstract = {To what extent the growth dynamics of tumors is controlled by nutrients, biomechanical forces and other factors at different stages and in different environments is still largely unknown. Here we present a biophysical model to study the spatio-temporal growth dynamics of two-dimensional tumor monolayers and three-dimensional tumor spheroids as a complementary tool to in vitro experiments. Within our model each cell is represented as an individual object and parametrized by cell-biophysical and cell-kinetic parameters that can all be experimentally determined. Hence our modeling strategy allows us to study which mechanisms on the microscopic level of individual cells may affect the macroscopic properties of a growing tumor. We find the qualitative growth kinetics and patterns at early growth stages to be remarkably robust. Quantitative comparisons between computer simulations using our model and published experimental observations on monolayer cultures suggest a biomechanically-mediated form of growth inhibition during the experimentally observed transition from exponential to sub-exponential growth at sufficiently large tumor sizes. Our simulations show that the same transition during the growth of avascular tumor spheroids can be explained largely by the same mechanism. Glucose (or oxygen) depletion seems to determine mainly the size of the necrotic core but not the size of the tumor. We explore the consequences of the suggested biomechanical form of contact inhibition, in order to permit an experimental test of our model. Based on our findings we propose a phenomenological growth law in early expansion phases in which specific biological small-scale processes are subsumed in a small number of effective parameters.},
langid = {english},
file = {/home/guillaume/Zotero/storage/FDDW7MW6/Drasdo et Höhme - 2005 - A single-cell-based model of tumor growthin vitro.pdf}
}
@article{dufourDecipheringTissueMorphodynamics2017,
title = {Deciphering Tissue Morphodynamics Using Bioimage Informatics},
author = {Dufour, Alexandre C. and Jonker, Anneliene H. and Olivo-Marin, Jean-Christophe},
date = {2017-05-19},
journaltitle = {Philos. Trans. R. Soc. Lond., B, Biol. Sci.},
volume = {372},
number = {1720},
eprint = {28348249},
eprinttype = {pmid},
issn = {1471-2970},
doi = {10.1098/rstb.2015.0512},
abstract = {In recent years developmental biology has greatly benefited from the latest advances in fluorescence microscopy techniques. Consequently, quantitative and automated analysis of this data is becoming a vital first step in the quest for novel insights into the various aspects of development. Here we present an introductory overview of the various image analysis methods proposed for developmental biology images, with particular attention to openly available software packages. These tools, as well as others to come, are rapidly paving the way towards standardized and reproducible bioimaging studies at the whole-tissue level. Reflecting on these achievements, we discuss the remaining challenges and the future endeavours lying ahead in the post-image analysis era.This article is part of the themed issue 'Systems morphodynamics: understanding the development of tissue hardware'.},
langid = {english},
pmcid = {PMC5379021},
keywords = {bioimage informatics,cell segmentation,cell tracking,Developmental Biology,Image Processing; Computer-Assisted,Microscopy; Fluorescence,Morphogenesis,Plant Development,reproducible research,software,Software}
}
@article{egan_role_????,
title = {The Role of Mechanics in Biological and Bio-Inspired Systems.},
author = {Egan, Paul and Sinko, Robert and LeDuc, Philip R and Keten, Sinan},
year = {January},
journaltitle = {Nature communications},
volume = {6},
eprint = {26145480},
eprinttype = {pmid},
pages = {7418},
issn = {2041-1723},
doi = {10.1038/ncomms8418},
url = {http://www.nature.com.gate1.inist.fr/ncomms/2015/150706/ncomms8418/full/ncomms8418.html},
abstract = {Natural systems frequently exploit intricate multiscale and multiphasic structures to achieve functionalities beyond those of man-made systems. Although understanding the chemical make-up of these systems is essential, the passive and active mechanics within biological systems are crucial when considering the many natural systems that achieve advanced properties, such as high strength-to-weight ratios and stimuli-responsive adaptability. Discovering how and why biological systems attain these desirable mechanical functionalities often reveals principles that inform new synthetic designs based on biological systems. Such approaches have traditionally found success in medical applications, and are now informing breakthroughs in diverse frontiers of science and engineering.},
langid = {english}
}
@article{ellenbergCallPublicArchives2018,
title = {A Call for Public Archives for Biological Image Data},
author = {Ellenberg, Jan and Swedlow, Jason R. and Barlow, Mary and Cook, Charles E. and Sarkans, Ugis and Patwardhan, Ardan and Brazma, Alvis and Birney, Ewan},
date = {2018-11},
journaltitle = {Nat. Methods},
volume = {15},
number = {11},
eprint = {30377375},
eprinttype = {pmid},
pages = {849--854},
issn = {1548-7105},
doi = {10.1038/s41592-018-0195-8},
langid = {english},
pmcid = {PMC6884425},
keywords = {Archives,Databases as Topic,Diagnostic Imaging,Humans,Image Processing; Computer-Assisted,Information Dissemination,Information Storage and Retrieval,Public Sector},
file = {/home/guillaume/Zotero/storage/QUGBPJ2Y/Ellenberg et al. - 2018 - A call for public archives for biological image da.pdf}
}
@article{elosegui-artola_mechanical_2016,
title = {Mechanical Regulation of a Molecular Clutch Defines Force Transmission and Transduction in Response to Matrix Rigidity.},
author = {Elosegui-Artola, Alberto and Oria, Roger and Chen, Yunfeng and Kosmalska, Anita and Pérez-González, Carlos and Castro, Natalia and Zhu, Cheng and Trepat, Xavier and Roca-Cusachs, Pere},
date = {2016-04},
journaltitle = {Nature cell biology},