You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
Copy file name to clipboardExpand all lines: participants/IgTRrefWGS.md
+2-2Lines changed: 2 additions & 2 deletions
Display the source diff
Display the rich diff
Original file line number
Diff line number
Diff line change
@@ -1,5 +1,5 @@
1
1
---
2
-
title: Transplantation Immunobiology Group, Central Clinical School, The University of Sydney
2
+
title: Transplantation Immunobiology Group, Central Clinical School, The University of Sydney
3
3
description: Defining accurate strain-specific germline references is an essential tool for understanding the development of B and T cells during immune responses. We are producing a haplotype-resolved Immunoglobulin and T cell receptor germline reference assembly using high-fidelity whole genome sequencing on BALB/c and B10.BR mice, followed by de-novo reference assembly, contig-alignment and annotation.
4
4
toc: false
5
5
type: ABLeS Participant
@@ -44,4 +44,4 @@ Our work will result in haplotype-resolved Immunoglobulin and T cell receptor ge
44
44
45
45
<br/>
46
46
47
-
> *These details have been provided by project members at project initiation. For more information on the project, please consult the contact(s) or project links above.*
47
+
> _These details have been provided by project members at project initiation. For more information on the project, please consult the contact(s) or project links above._
Copy file name to clipboardExpand all lines: participants/NSWPToL.md
+7-7Lines changed: 7 additions & 7 deletions
Display the source diff
Display the rich diff
Original file line number
Diff line number
Diff line change
@@ -1,5 +1,5 @@
1
1
---
2
-
title: Botanic Gardens of Sydney;
2
+
title: Botanic Gardens of Sydney;
3
3
description: We aim to use the Angiosperms353 target capture methodology to sequence every native NSW flowering plant species during stage one of our Phylogenomic Flagship project (about 7000 species and subspecies).
4
4
toc: false
5
5
type: ABLeS Participant
@@ -41,16 +41,16 @@ This work is supported through the reference data asset creation scheme provided
41
41
42
42
A phylogenomic Angiosperms353 nuclear gene dataset for all 7000 plant species (and infrataxa) of NSW. Assembly, alignments, and trees constructed from this dataset will be used to construct the NSWPToL. Important milestones and outputs includes:
43
43
44
-
1) pilot and proof of concept: The Australian Botanic Gardens Mount Annan Tree of Life;
44
+
1. pilot and proof of concept: The Australian Botanic Gardens Mount Annan Tree of Life;
45
45
46
-
2) phylogenomic compendium for all species described on PlantNET (e.g., a state recognised phylogenetic dataset for identification purposes);
46
+
2. phylogenomic compendium for all species described on PlantNET (e.g., a state recognised phylogenetic dataset for identification purposes);
47
47
48
-
3) publication of the NSWPToL;
48
+
3. publication of the NSWPToL;
49
49
50
-
4) multiple publications identifying systematics of NSW groups and taxonomic changes supported by the NSWPToL;
50
+
4. multiple publications identifying systematics of NSW groups and taxonomic changes supported by the NSWPToL;
51
51
52
-
5) public outreach talks, science seminars, and national and international conference communications. All new genomic DNA sequence data generated by the NSWPToL will eventually be released publicly to international genomic repositories (e.g., European Nucleotide Archive) and legacy web portals (e.g., Kew Tree of Life Explorer).
52
+
5. public outreach talks, science seminars, and national and international conference communications. All new genomic DNA sequence data generated by the NSWPToL will eventually be released publicly to international genomic repositories (e.g., European Nucleotide Archive) and legacy web portals (e.g., Kew Tree of Life Explorer).
53
53
54
54
<br/>
55
55
56
-
> *These details have been provided by project members at project initiation. For more information on the project, please consult the contact(s) or project links above.*
56
+
> _These details have been provided by project members at project initiation. For more information on the project, please consult the contact(s) or project links above._
Copy file name to clipboardExpand all lines: participants/adapts.md
+2-2Lines changed: 2 additions & 2 deletions
Display the source diff
Display the rich diff
Original file line number
Diff line number
Diff line change
@@ -1,5 +1,5 @@
1
1
---
2
-
title: Cancer Signalling Research Group, School of Biomedical Sciences & Pharmacy, University of Newcastle.
2
+
title: Cancer Signalling Research Group, School of Biomedical Sciences & Pharmacy, University of Newcastle.
3
3
description: Development of DMG ADvanced mAchine learning Precision Treatment Strategy (ADAPTS) platform. This project aims to model temporal tumour adaptations to therapy and predict targetable vulnerabilities, based on non-invasive blood profiling, for therapeutic adjustments of patients with DMG under treatment.
4
4
toc: false
5
5
type: ABLeS Participant
@@ -65,4 +65,4 @@ A public ADAPTS platform, featuring computational workflows developed on [GitHub
65
65
66
66
<br/>
67
67
68
-
> *These details have been provided by project members at project initiation. For more information on the project, please consult the contact(s) or project links above.*
68
+
> _These details have been provided by project members at project initiation. For more information on the project, please consult the contact(s) or project links above._
The [Australian Amphibian and Reptile Genomics Initiative (AusARG)](https://ausargenomics.com/) is a national collaborative project that will facilitate research using genomics approaches towards a more thorough understanding of evolution and conservation of Australia’s unique native amphibians and reptiles that are now under threat, through climate, disease or habitat modification.
25
22
26
23
AusARG's mission is to build genomic resources to understand and protect Australia’s reptiles and amphibians.
27
24
28
-
+ Reference genomes
29
-
+ Phylogenomics
30
-
+ Conservation and Taxonomy genomics
25
+
- Reference genomes
26
+
- Phylogenomics
27
+
- Conservation and Taxonomy genomics
31
28
32
29
[GitHub link](https://github.com/AusARG)
33
30
34
-
35
31
## How is ABLeS supporting this work?
36
32
37
33
This work is supported through the reference data asset creation scheme provided by ABLeS. The support includes 135 TB long term storage, 1 TB temoprary storage on scratch and 100 KSUs per quarter.
@@ -40,4 +36,4 @@ This work is supported through the reference data asset creation scheme provided
40
36
41
37
<br/>
42
38
43
-
> *These details have been provided by project members at project initiation. For more information on the project, please consult the contact(s) or project links above.*
39
+
> _These details have been provided by project members at project initiation. For more information on the project, please consult the contact(s) or project links above._
Copy file name to clipboardExpand all lines: participants/benchmarking.md
+4-6Lines changed: 4 additions & 6 deletions
Display the source diff
Display the rich diff
Original file line number
Diff line number
Diff line change
@@ -2,7 +2,7 @@
2
2
title: Walter and Eliza Hall Institute of Medical Research (WEHI)
3
3
description: This project will help life-science researchers improve the estimation of their grants and compute resources by creating a portable and rerunnable pipeline that benchmarks commonly used life-science analysis software.
4
4
toc: false
5
-
type: ABLeS Participant
5
+
type: ABLeS Participant - Completed
6
6
---
7
7
8
8
## Project title
@@ -17,16 +17,14 @@ Benchmarking life science software on national and institutional HPC platforms.
Software is critical to the life sciences, and performance of that software is needed for planning of projects, such as predicting funding, applying for grants, and assessing hardware. This project aims to deliver a portable, automated, and configurable pipeline that can be used repeatedly by life science researchers to plan their workloads and test their hardware.
29
-
27
+
Software is critical to the life sciences, and performance of that software is needed for planning of projects, such as predicting funding, applying for grants, and assessing hardware. This project aims to deliver a portable, automated, and configurable pipeline that can be used repeatedly by life science researchers to plan their workloads and test their hardware.
30
28
31
29
## How is ABLeS supporting this work?
32
30
@@ -41,4 +39,4 @@ Benchmarking results to be made public (publication platform TBC).
41
39
42
40
<br/>
43
41
44
-
> *These details have been provided by project members at project initiation. For more information on the project, please consult the contact(s) or project links above.*
42
+
> _These details have been provided by project members at project initiation. For more information on the project, please consult the contact(s) or project links above._
Copy file name to clipboardExpand all lines: participants/ciehf.md
+3-3Lines changed: 3 additions & 3 deletions
Display the source diff
Display the rich diff
Original file line number
Diff line number
Diff line change
@@ -1,5 +1,5 @@
1
1
---
2
-
title: ARC Centre of Excellence for Indigenous and Environmental Histories and Futures (CIEHF).
2
+
title: ARC Centre of Excellence for Indigenous and Environmental Histories and Futures (CIEHF).
3
3
description: This project aims to advance sedimentary ancient DNA (sedaDNA) research in Australia by developing an automated bioinformatics pipeline for efficient and validated taxonomic profiling of modern and ancient target taxa in sediment samples.
4
4
toc: false
5
5
type: ABLeS Participant
@@ -12,7 +12,7 @@ Reconstructing Australian paleoenvironments and biodiversity using metagenomic a
12
12
## Collaborators and funding
13
13
14
14
- ARC Centre for Excellence for Indigenous and Environmental Histories and Futures
15
-
(CIEHF)
15
+
(CIEHF)
16
16
17
17
- Australian Centre for Ancient DNA, University of Adelaide
18
18
@@ -56,4 +56,4 @@ consultation with our Indigenous partners.
56
56
57
57
<br/>
58
58
59
-
> *These details have been provided by project members at project initiation. For more information on the project, please consult the contact(s) or project links above.*
59
+
> _These details have been provided by project members at project initiation. For more information on the project, please consult the contact(s) or project links above._
Copy file name to clipboardExpand all lines: participants/cotton.md
+2-2Lines changed: 2 additions & 2 deletions
Display the source diff
Display the rich diff
Original file line number
Diff line number
Diff line change
@@ -17,7 +17,7 @@ The project was funded by Bioplatforms Australia.
17
17
## Contact(s)
18
18
19
19
- Ignatius Pang, Australian Proteome Analysis Facility (APAF), <[email protected]>
20
-
- Brian Atwell, School of Natural Sciences, Macquarie University, <[email protected]>
20
+
- Brian Atwell, School of Natural Sciences, Macquarie University, <[email protected]>
21
21
22
22
## Project description and aims
23
23
@@ -29,7 +29,7 @@ This work is supported through the production bioinformatics scheme provided by
29
29
30
30
## Expected outputs enabled by participation in ABLeS
31
31
32
-
The outcome research will be written as a manuscript and submitted to a peer reviewed journal for publication. The assembled genome and protein annotations will be submitted to public genomics repository (e.g. NCBI’s databases).
32
+
The outcome research will be written as a manuscript and submitted to a peer reviewed journal for publication. The assembled genome and protein annotations will be submitted to public genomics repository (e.g. NCBI’s databases).
The Structural Biology Node will explore software and hardware efficiencies in the current deep learning revolution in computational structural biology. Pawsey's architecture provides a unique testing ground for structural biology software on high performance computing (HPC). These findings will be shared with local and national HPC facilities, the steering committee, and scientific advisory board in order to formulate best-practice in this new style of compute for biomolecular structures, and drive widespread adoption by biochemical/medical researchers in Australia.
27
+
The Structural Biology Node will explore software and hardware efficiencies in the current deep learning revolution in computational structural biology. Pawsey's architecture provides a unique testing ground for structural biology software on high performance computing (HPC). These findings will be shared with local and national HPC facilities, the steering committee, and scientific advisory board in order to formulate best-practice in this new style of compute for biomolecular structures, and drive widespread adoption by biochemical/medical researchers in Australia.
31
28
29
+
Aims:
32
30
33
-
Aims:
34
-
- Benchmarking AlphaFold variants (e.g. [`OpenFold`](https://doi.org/10.1101/2022.11.20.517210), [`FastFold`](https://doi.org/10.48550/arXiv.2203.00854)) and optimising their use on HPC facilities
35
-
- Apply protein generative AI (e.g. [`RFDiffusion`](https://doi.org/10.1038/s41586-023-06415-8), [`EvoDiff`](https://doi.org/10.1101/2023.09.11.556673), [`ProteinMPNN`](https://doi.org/10.1101/2022.06.03.494563)) for generation of novel protein designs that can be used in fundamental biology and therapeutic research
31
+
- Benchmarking AlphaFold variants (e.g. [`OpenFold`](https://doi.org/10.1101/2022.11.20.517210), [`FastFold`](https://doi.org/10.48550/arXiv.2203.00854)) and optimising their use on HPC facilities
32
+
- Apply protein generative AI (e.g. [`RFDiffusion`](https://doi.org/10.1038/s41586-023-06415-8), [`EvoDiff`](https://doi.org/10.1101/2023.09.11.556673), [`ProteinMPNN`](https://doi.org/10.1101/2022.06.03.494563)) for generation of novel protein designs that can be used in fundamental biology and therapeutic research
36
33
- Validating compilation of CUDA code of the above software onto AMD GPUs.
37
34
38
35
## How is ABLeS supporting this work?
@@ -43,7 +40,6 @@ This work is supported through the production bioinformatics scheme provided by
43
40
44
41
This project enables the Structural Biology Node to be responsive to the deep learning developments in computational structural biology. The repurposing and application of AI methods to biological problems is producing pre-print code at a rapid rate, many of these methods find eventual publication in top-rank journals. This is the beginning of software explosion in this ecosystem, and so we will be continually validating new code on the leading-edge for wide use by the biological research community. Findings will be shared to the wider community and may ouput publications in technical proceedings.
45
42
46
-
47
43
<br/>
48
44
49
-
> *These details have been provided by project members at project initiation. For more information on the project, please consult the contact(s) or project links above.*
45
+
> _These details have been provided by project members at project initiation. For more information on the project, please consult the contact(s) or project links above._
Copy file name to clipboardExpand all lines: participants/diann.md
+4-6Lines changed: 4 additions & 6 deletions
Display the source diff
Display the rich diff
Original file line number
Diff line number
Diff line change
@@ -19,17 +19,16 @@ Development and optimisation of a DIA-NN workflow for scalable proteomics
19
19
20
20
- Cali Willet, Sydney Informatics Hub, University of Sydney <[email protected]>
21
21
22
-
- Carsten Schmitz-Peiffer, Charles Perkins Center, University of Sydney <[email protected]>
22
+
- Carsten Schmitz-Peiffer, Charles Perkins Center, University of Sydney <[email protected]>
23
23
24
24
- Lewin Small, Charles Perkins Center, University of Sydney, <[email protected]>
25
25
26
26
- Georgie Samaha, Sydney Informatics Hub, University of Sydney <[email protected]>
27
27
28
-
29
28
## Project description and aims
30
29
31
-
Scanning SWATH is a novel method that now enables rapid mass spectrometry of hundreds of peptide samples.DIA-NN is a popular tool for processing data-independent acquisition (DIA) proteomics experiments.
32
-
However, throughput of DIA-NN is currently limited and processing large cohorts requires days of computing time and batch processing.
30
+
Scanning SWATH is a novel method that now enables rapid mass spectrometry of hundreds of peptide samples.DIA-NN is a popular tool for processing data-independent acquisition (DIA) proteomics experiments.
31
+
However, throughput of DIA-NN is currently limited and processing large cohorts requires days of computing time and batch processing.
33
32
We will develop a scalable bioinformatics workflow that optimises the execution of DIA-NN for execution on high-performance computing infrastructure and commercial cloud to meet the growing demand of high-throughput proteomics experiments
34
33
35
34
The workflow will enable rapid generation of unbiased quantitative data concerning the proteins present in high numbers of complex tissue samples, obtained for example under different dietary or genetic conditions. This will enable further mechanistic investigation of the phenotypes observed.
@@ -44,7 +43,6 @@ This work is supported through the software accelerator scheme provided by ABLeS
44
43
45
44
A computational workflow for DIA-NN software-based processing of scanning SWATH data. The workflow development can be followed on [GitHub](https://github.com/Sydney-Informatics-Hub/Scalable-DIA-NN).
46
45
47
-
48
46
<br/>
49
47
50
-
> *These details have been provided by project members at project initiation. For more information on the project, please consult the contact(s) or project links above.*
48
+
> _These details have been provided by project members at project initiation. For more information on the project, please consult the contact(s) or project links above._
0 commit comments