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<!DOCTYPE html>
<html lang="en">
<head>
<meta charset="UTF-8">
<meta name="viewport" content="width=device-width, initial-scale=1.0">
<title>ISB Datasets</title>
<link rel="stylesheet" href="css/style.css">
</head>
<body>
<header>
<div class="header-content">
<img src="images/scilifelab-logo.png" alt="SciLifeLab Logo" class="scilifelab-logo">
<h1>ISB Datasets</h1>
<p>Manually Curated Integrated Structural Biology Multi-Technique Datasets</p>
</div>
</header>
<nav>
<div class="nav-content">
<div class="nav-left">
<a href="index.html">Home</a>
<a href="about.html">About</a>
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<div class="nav-right">
<!-- Filter Section (Collapsible) -->
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<!-- Technique Combination Heatmap -->
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<span>Technique Matrix</span>
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<!-- Search Section -->
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<label for="search-input" class="search-label">Search by protein name, organism, or description</label>
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<input type="text" id="search-input" class="search-input" placeholder="Search by protein name, organism, or description...">
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<h3>Filter by Technique</h3>
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<span id="result-count">35</span> datasets shown
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<!-- Heatmap Section Dropdown -->
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<p class="heatmap-description">
This matrix shows how many datasets contain each pair of techniques.
Click a cell to filter datasets by that combination.
</p>
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<!-- Heatmap will be generated by JavaScript -->
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<div class="heatmap-legend">
<span class="legend-label">Datasets:</span>
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<span class="legend-item legend-1">1</span>
<span class="legend-item legend-2">2</span>
<span class="legend-item legend-3">3+</span>
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</nav>
<div class="container">
<p class="index-intro">Browse integrated structural biology datasets combining multiple experimental and computational techniques.</p>
<div class="dataset-grid">
<!-- Dataset 1: GLIC lipid-binding & gating -->
<div class="dataset-card">
<h3><a href="datasets/dataset-1.html">GLIC lipid-binding & gating</a></h3>
<div class="dataset-meta">
<strong>Organism:</strong> Gloeobacter violaceus<br>
<strong>Years:</strong> ~2019–2023<br>
<strong>Status:</strong> Public
</div>
<div class="dataset-description">
Pentameric ligand-gated ion channel GLIC; cryo-EM structures in nanodiscs, lipid binding analysis, integrated with MD and earlier X-ray/SANS.
</div>
<div class="techniques">
<span class="technique-badge">Cryo-EM</span>
<span class="technique-badge">X-ray</span>
<span class="technique-badge">SANS</span>
<span class="technique-badge">Biophysics</span>
<span class="technique-badge">MD</span>
<span class="technique-badge">Modelling</span>
</div>
</div>
<!-- Dataset 2: DeCLIC Ca²⁺-stabilised N-terminal domain -->
<div class="dataset-card">
<h3><a href="datasets/dataset-2.html">DeCLIC Ca²⁺-stabilised N-terminal domain</a></h3>
<div class="dataset-meta">
<strong>Organism:</strong> Bacterial pLGIC (DeCLIC)<br>
<strong>Years:</strong> ~2022–2025<br>
<strong>Status:</strong> Public
</div>
<div class="dataset-description">
Pentameric ion channel DeCLIC with accessory N-terminal domain; cryo-EM structures in nanodiscs, Ca²⁺ binding in NTD and ECD, interpreted with previous SAS and MD.
</div>
<div class="techniques">
<span class="technique-badge">Cryo-EM</span>
<span class="technique-badge">SAXS</span>
<span class="technique-badge">Biophysics</span>
<span class="technique-badge">MD</span>
<span class="technique-badge">Modelling</span>
</div>
</div>
<!-- Dataset 3: MUC2 CysD2 domain -->
<div class="dataset-card">
<h3><a href="datasets/dataset-3.html">MUC2 CysD2 domain</a></h3>
<div class="dataset-meta">
<strong>Organism:</strong> Human MUC2 domain<br>
<strong>Years:</strong> ~2021–2024<br>
<strong>Status:</strong> Public
</div>
<div class="dataset-description">
Second CysD domain (CysD2) from intestinal mucin MUC2; NMR solution structure, SAXS and MS/MST to understand mucin network organisation and cross-linking.
</div>
<div class="techniques">
<span class="technique-badge">SAXS</span>
<span class="technique-badge">NMR</span>
<span class="technique-badge">MS / Proteomics</span>
<span class="technique-badge">Biophysics</span>
<span class="technique-badge">Modelling</span>
</div>
</div>
<!-- Dataset 4: MecA/ClpC/ClpP AAA⁺ protease -->
<div class="dataset-card">
<h3><a href="datasets/dataset-4.html">MecA/ClpC/ClpP AAA⁺ protease</a></h3>
<div class="dataset-meta">
<strong>Organism:</strong> Staphylococcus aureus<br>
<strong>Years:</strong> ~2022–2025<br>
<strong>Status:</strong> Public
</div>
<div class="dataset-description">
Central AAA⁺ protease MecA/ClpC/ClpP from S. aureus; near-atomic cryo-EM structure, integrated with AF modelling and functional assays.
</div>
<div class="techniques">
<span class="technique-badge">Cryo-EM</span>
<span class="technique-badge">MS / Proteomics</span>
<span class="technique-badge">Biophysics</span>
<span class="technique-badge">Modelling</span>
</div>
</div>
<!-- Dataset 5: FusB-mediated rescue of EF-G from fusidic acid -->
<div class="dataset-card">
<h3><a href="datasets/dataset-5.html">FusB-mediated rescue of EF-G from fusidic acid</a></h3>
<div class="dataset-meta">
<strong>Organism:</strong> Bacterial 70S ribosome, EF-G, FusB<br>
<strong>Years:</strong> ~2022–2024<br>
<strong>Status:</strong> Public
</div>
<div class="dataset-description">
Ribosome-bound EF-G stalled by fusidic acid and rescued by FusB; time-resolved cryo-EM "movie" combined with kinetics and MS quantification.
</div>
<div class="techniques">
<span class="technique-badge">Cryo-EM</span>
<span class="technique-badge">MS / Proteomics</span>
<span class="technique-badge">Biophysics</span>
<span class="technique-badge">Modelling</span>
</div>
</div>
<!-- Dataset 6: Sodium caprate scattering + CG-MD -->
<div class="dataset-card">
<h3><a href="datasets/dataset-6.html">Sodium caprate scattering + CG-MD</a></h3>
<div class="dataset-meta">
<strong>Organism:</strong> Small molecule surfactant (C10)<br>
<strong>Years:</strong> ~2023–2025<br>
<strong>Status:</strong> Public
</div>
<div class="dataset-description">
Sodium caprate (C10) aggregation; small-angle scattering data and final CG-MD snapshots for multiple conditions, packaged as one dataset.
</div>
<div class="techniques">
<span class="technique-badge">SAXS</span>
<span class="technique-badge">SANS</span>
<span class="technique-badge">MD</span>
</div>
</div>
<!-- Dataset 7: Spatial Multimodal Analysis (SMA) -->
<div class="dataset-card">
<h3><a href="datasets/dataset-7.html">Spatial Multimodal Analysis (SMA) - Spatial Transcriptomics</a></h3>
<div class="dataset-meta">
<strong>Organism:</strong> Human/Mouse tissue samples<br>
<strong>Years:</strong> ~2022–2024<br>
<strong>Status:</strong> Public
</div>
<div class="dataset-description">
Spatial transcriptomics data matched with MALDI-MSI for comprehensive tissue section analysis; 19 tissue sections combining gene expression and molecular distribution.
</div>
<div class="techniques">
<span class="technique-badge">Spatial Transcriptomics</span>
<span class="technique-badge">MS / Proteomics</span>
<span class="technique-badge">Bioinformatics</span>
</div>
</div>
<!-- Dataset 9: Yeast Nuclear Pore Complex - CX-MS -->
<div class="dataset-card">
<h3><a href="datasets/dataset-9.html">Yeast Nuclear Pore Complex - CX-MS</a></h3>
<div class="dataset-meta">
<strong>Organism:</strong> Saccharomyces cerevisiae<br>
<strong>Years:</strong> ~2020–2021<br>
<strong>Status:</strong> Public
</div>
<div class="dataset-description">
Comprehensive structure and functional adaptations of the yeast nuclear pore complex using cross-linking mass spectrometry and integrative modeling.
</div>
<div class="techniques">
<span class="technique-badge">MS / Proteomics</span>
<span class="technique-badge">Cryo-EM</span>
<span class="technique-badge">Modelling</span>
</div>
</div>
<!-- Dataset 10: Epitope Mapping with Sidewinder -->
<div class="dataset-card">
<h3><a href="datasets/dataset-10.html">Epitope Mapping with Sidewinder - XL-MS and Structural Modeling</a></h3>
<div class="dataset-meta">
<strong>Organism:</strong> Streptococcal antigens / human IgG<br>
<strong>Years:</strong> ~2023–2025<br>
<strong>Status:</strong> Public
</div>
<div class="dataset-description">
Epitope mapping combining cross-linking mass spectrometry (XL-MS) with structural modeling; Sidewinder approach for identification and structural interpretation of protein epitopes.
</div>
<div class="techniques">
<span class="technique-badge">MS / Proteomics</span>
<span class="technique-badge">Modelling</span>
</div>
</div>
<!-- Dataset 11: Multimodal MS Streptolysin O -->
<div class="dataset-card">
<h3><a href="datasets/dataset-11.html">Multimodal Mass Spectrometry - S. pyogenes Streptolysin O epitope</a></h3>
<div class="dataset-meta">
<strong>Organism:</strong> Streptococcus pyogenes<br>
<strong>Years:</strong> ~2023–2024<br>
<strong>Status:</strong> Public
</div>
<div class="dataset-description">
Multimodal mass spectrometry identifies a conserved protective epitope in S. pyogenes Streptolysin O; combines multiple MS strategies for epitope discovery and validation.
</div>
<div class="techniques">
<span class="technique-badge">MS / Proteomics</span>
<span class="technique-badge">Biophysics</span>
<span class="technique-badge">Modelling</span>
</div>
</div>
<!-- Dataset 12: S. pyogenes M1 integrative structural biology -->
<div class="dataset-card">
<h3><a href="datasets/dataset-12.html">S. pyogenes M1 protein - integrative structural biology</a></h3>
<div class="dataset-meta">
<strong>Organism:</strong> S. pyogenes M1 / Human IgG<br>
<strong>Years:</strong> ~2019–2021<br>
<strong>Status:</strong> Public
</div>
<div class="dataset-description">
Structural determination of M1 protein interactions with human IgG using integrative structural biology; XL-MS, HDX-MS and computational modelling.
</div>
<div class="techniques">
<span class="technique-badge">MS / Proteomics</span>
<span class="technique-badge">Biophysics</span>
<span class="technique-badge">Modelling</span>
</div>
</div>
<!-- Dataset 13: In vivo XL-MS Complement MAC -->
<div class="dataset-card">
<h3><a href="datasets/dataset-13.html">In vivo Cross-Linking MS - Complement MAC on Gram-positive bacteria</a></h3>
<div class="dataset-meta">
<strong>Organism:</strong> Gram-positive bacteria / Human complement MAC<br>
<strong>Years:</strong> ~2019–2020<br>
<strong>Status:</strong> Public
</div>
<div class="dataset-description">
In vivo cross-linking mass spectrometry of the Complement System MAC assembled on live Gram-positive bacteria; structural proteomics in native context.
</div>
<div class="techniques">
<span class="technique-badge">MS / Proteomics</span>
<span class="technique-badge">Modelling</span>
</div>
</div>
<!-- Dataset 14: IgG against streptococcal pathogens -->
<div class="dataset-card">
<h3><a href="datasets/dataset-14.html">Circulating IgG against streptococcal pathogens - systems antigenomics-serology</a></h3>
<div class="dataset-meta">
<strong>Organism:</strong> S. pyogenes / Human IgG<br>
<strong>Years:</strong> ~2023–2025<br>
<strong>Status:</strong> Public
</div>
<div class="dataset-description">
Combined systems antigenomics-serology workflow for dissecting circulating IgG against streptococcal pathogens.
</div>
<div class="techniques">
<span class="technique-badge">MS / Proteomics</span>
<span class="technique-badge">Modelling</span>
<span class="technique-badge">Bioinformatics</span>
</div>
</div>
<!-- Dataset 15: Streptolysin O plasminogen -->
<div class="dataset-card">
<h3><a href="datasets/dataset-15.html">Streptolysin O accelerates plasminogen to plasmin</a></h3>
<div class="dataset-meta">
<strong>Organism:</strong> S. pyogenes / Human plasminogen<br>
<strong>Years:</strong> ~2022–2024<br>
<strong>Status:</strong> Public
</div>
<div class="dataset-description">
Structural proteomics and kinetics of Streptolysin O accelerating plasminogen-to-plasmin conversion.
</div>
<div class="techniques">
<span class="technique-badge">MS / Proteomics</span>
<span class="technique-badge">Biophysics</span>
<span class="technique-badge">Modelling</span>
</div>
</div>
<!-- Dataset 16: AP + XL-MS host-pathogen -->
<div class="dataset-card">
<h3><a href="datasets/dataset-16.html">Affinity-Purification combined with Crosslinking MS for host–pathogen complexes</a></h3>
<div class="dataset-meta">
<strong>Organism:</strong> Host–pathogen systems<br>
<strong>Years:</strong> ~2020–2023<br>
<strong>Status:</strong> Public
</div>
<div class="dataset-description">
AP combined with XL-MS for identification and structural modeling of host–pathogen protein–protein complexes.
</div>
<div class="techniques">
<span class="technique-badge">MS / Proteomics</span>
<span class="technique-badge">Modelling</span>
</div>
</div>
<!-- Dataset 17: Actin/tubulin in TRiC -->
<div class="dataset-card">
<h3><a href="datasets/dataset-17.html">Actin and tubulin folding inside the TRiC chaperonin</a></h3>
<div class="dataset-meta">
<strong>Organism:</strong> Human actin/tubulin / TRiC<br>
<strong>Years:</strong> ~2020–2022<br>
<strong>Status:</strong> Public
</div>
<div class="dataset-description">
Snapshots of actin and tubulin folding inside the TRiC chaperonin; near-atomic cryo-EM structures.
</div>
<div class="techniques">
<span class="technique-badge">Cryo-EM</span>
<span class="technique-badge">Modelling</span>
</div>
</div>
<!-- Dataset 18: Sec61/TRAP translocon -->
<div class="dataset-card">
<h3><a href="datasets/dataset-18.html">ER membrane remodeling by Sec61/TRAP translocon</a></h3>
<div class="dataset-meta">
<strong>Organism:</strong> Mammalian Sec61/TRAP<br>
<strong>Years:</strong> ~2021–2023<br>
<strong>Status:</strong> Public
</div>
<div class="dataset-description">
Molecular view of ER membrane remodeling by the Sec61/TRAP translocon; cryo-EM + MD.
</div>
<div class="techniques">
<span class="technique-badge">Cryo-EM</span>
<span class="technique-badge">MD</span>
<span class="technique-badge">Modelling</span>
</div>
</div>
<!-- Dataset 19: ApoA-I HDX -->
<div class="dataset-card">
<h3><a href="datasets/dataset-19.html">ApoA-I amyloidogenic variants - structure dynamics in small HDL</a></h3>
<div class="dataset-meta">
<strong>Organism:</strong> Human ApoA-I / HDL<br>
<strong>Years:</strong> ~2019–2020<br>
<strong>Status:</strong> Public
</div>
<div class="dataset-description">
HDX-MS and structural analysis of ApoA-I amyloidogenic variants in small HDL; cholesterol efflux.
</div>
<div class="techniques">
<span class="technique-badge">MS / Proteomics</span>
<span class="technique-badge">Biophysics</span>
<span class="technique-badge">Modelling</span>
</div>
</div>
<!-- Dataset 20: N-Myc Aurora A -->
<div class="dataset-card">
<h3><a href="datasets/dataset-20.html">N-Myc MB0-MBI region with Aurora kinase A</a></h3>
<div class="dataset-meta">
<strong>Organism:</strong> Human N-Myc / Aurora A<br>
<strong>Years:</strong> ~2020–2022<br>
<strong>Status:</strong> Public
</div>
<div class="dataset-description">
N-Myc MB0-MBI region interacts with Aurora kinase A N-lobe; multitechnique structural and proteomics.
</div>
<div class="techniques">
<span class="technique-badge">MS / Proteomics</span>
<span class="technique-badge">Biophysics</span>
<span class="technique-badge">Modelling</span>
</div>
</div>
<!-- Dataset 21: Glucosinolate diversity -->
<div class="dataset-card">
<h3><a href="datasets/dataset-21.html">Glucosinolate diversity in Brassicaceae – MS and NMR</a></h3>
<div class="dataset-meta">
<strong>Organism:</strong> Brassicaceae (field-collected)<br>
<strong>Years:</strong> ~2024–2025<br>
<strong>Status:</strong> Public
</div>
<div class="dataset-description">
Multimodal MS and NMR profiling of glucosinolate diversity across seven Brassicaceae species.
</div>
<div class="techniques">
<span class="technique-badge">MS / Proteomics</span>
<span class="technique-badge">NMR</span>
</div>
</div>
<!-- Dataset 22: Immune cell EVs -->
<div class="dataset-card">
<h3><a href="datasets/dataset-22.html">Proteomic and lipidomic profiling of immune cell-derived EVs</a></h3>
<div class="dataset-meta">
<strong>Organism:</strong> Human immune cells<br>
<strong>Years:</strong> ~2024–2026<br>
<strong>Status:</strong> Public
</div>
<div class="dataset-description">
Multimodal proteomics, lipidomics and microscopy of extracellular vesicle subpopulations.
</div>
<div class="techniques">
<span class="technique-badge">MS / Proteomics</span>
<span class="technique-badge">Bioinformatics</span>
</div>
</div>
<!-- Dataset 23: CRESS-DNA bacilladnaviruses -->
<div class="dataset-card">
<h3><a href="datasets/dataset-23.html">CRESS-DNA bacilladnaviruses – cryo-EM and computational modelling</a></h3>
<div class="dataset-meta">
<strong>Organism:</strong> Bacilladnaviruses<br>
<strong>Years:</strong> ~2024–2025<br>
<strong>Status:</strong> Public
</div>
<div class="dataset-description">
Integrative cryo-EM and computational modelling of CRESS-DNA bacilladnavirus structure and diversity.
</div>
<div class="techniques">
<span class="technique-badge">Cryo-EM</span>
<span class="technique-badge">Modelling</span>
</div>
</div>
<!-- Dataset 24: Live fluorescence + cryo-ET -->
<div class="dataset-card">
<h3><a href="datasets/dataset-24.html">Live fluorescence imaging and cryo-ET of septation in Deinococcus radiodurans</a></h3>
<div class="dataset-meta">
<strong>Organism:</strong> Deinococcus radiodurans<br>
<strong>Years:</strong> ~2024–2025<br>
<strong>Status:</strong> Public
</div>
<div class="dataset-description">
Correlative live fluorescence imaging and in situ cryo-ET of bacterial septation.
</div>
<div class="techniques">
<span class="technique-badge">Cryo-EM</span>
<span class="technique-badge">Bioinformatics</span>
</div>
</div>
<!-- Dataset 25: IAPP mutant polymorphism -->
<div class="dataset-card">
<h3><a href="datasets/dataset-25.html">IAPP mutant polymorphism – cryo-EM and integrative analysis</a></h3>
<div class="dataset-meta">
<strong>Organism:</strong> Human IAPP (amylin)<br>
<strong>Years:</strong> ~2024–2025<br>
<strong>Status:</strong> Public
</div>
<div class="dataset-description">
Cryo-EM and computational analysis of IAPP fibril polymorphism for peptide-based therapeutics.
</div>
<div class="techniques">
<span class="technique-badge">Cryo-EM</span>
<span class="technique-badge">Modelling</span>
<span class="technique-badge">Bioinformatics</span>
</div>
</div>
<!-- Dataset 26: TBEV structure pathogenicity tropism -->
<div class="dataset-card">
<h3><a href="datasets/dataset-26.html">TBEV structure, pathogenicity and tropism – pre-membrane and envelope proteins</a></h3>
<div class="dataset-meta">
<strong>Organism:</strong> Tick-borne encephalitis virus<br>
<strong>Years:</strong> ~2024–2025<br>
<strong>Status:</strong> Public
</div>
<div class="dataset-description">
Cryo-EM combined with glycoproteomics for TBEV structural and functional characterisation.
</div>
<div class="techniques">
<span class="technique-badge">Cryo-EM</span>
<span class="technique-badge">MS / Proteomics</span>
</div>
</div>
<!-- Dataset 27: IAPP polymorphism cross-aggregation -->
<div class="dataset-card">
<h3><a href="datasets/dataset-27.html">IAPP solution-dependent polymorphism and cross-aggregation – cryo-EM and MALDI-MSI</a></h3>
<div class="dataset-meta">
<strong>Organism:</strong> Human / Rat IAPP<br>
<strong>Years:</strong> ~2024–2025<br>
<strong>Status:</strong> Public
</div>
<div class="dataset-description">
Cryo-EM with spatial mass spectrometry for IAPP fibril polymorphism and human–rat cross-aggregation.
</div>
<div class="techniques">
<span class="technique-badge">Cryo-EM</span>
<span class="technique-badge">MS / Proteomics</span>
<span class="technique-badge">Modelling</span>
</div>
</div>
<!-- Dataset 28: TBEV ACBD3 ER-Golgi -->
<div class="dataset-card">
<h3><a href="datasets/dataset-28.html">TBEV – ACBD3 coordinates ER-Golgi contacts for productive infection</a></h3>
<div class="dataset-meta">
<strong>Organism:</strong> TBEV / Mammalian cells<br>
<strong>Years:</strong> ~2024–2025<br>
<strong>Status:</strong> Public
</div>
<div class="dataset-description">
Multimodal cryo-EM, glycoproteomics and microscopy for TBEV–host interface.
</div>
<div class="techniques">
<span class="technique-badge">Cryo-EM</span>
<span class="technique-badge">MS / Proteomics</span>
<span class="technique-badge">Bioinformatics</span>
</div>
</div>
<!-- Dataset 29: MakA cytotoxin -->
<div class="dataset-card">
<h3><a href="datasets/dataset-29.html">MakA cytotoxin oligomerization – protein-lipid interaction at low pH</a></h3>
<div class="dataset-meta">
<strong>Organism:</strong> Vibrio cholerae (MakA)<br>
<strong>Years:</strong> ~2021–2022<br>
<strong>Status:</strong> Public
</div>
<div class="dataset-description">
Cryo-EM, microscopy and NMR for MakA cytotoxin structure and oligomerization.
</div>
<div class="techniques">
<span class="technique-badge">Cryo-EM</span>
<span class="technique-badge">NMR</span>
<span class="technique-badge">Modelling</span>
</div>
</div>
<!-- Dataset 30: Plasticized lignins -->
<div class="dataset-card">
<h3><a href="datasets/dataset-30.html">Plasticized lignins – NMR and SAXS</a></h3>
<div class="dataset-meta">
<strong>Organism:</strong> Lignin (plant-derived polymer)<br>
<strong>Years:</strong> ~2024–2025<br>
<strong>Status:</strong> Public
</div>
<div class="dataset-description">
NMR and SAXS for molecular-level characterisation of plasticized lignins.
</div>
<div class="techniques">
<span class="technique-badge">NMR</span>
<span class="technique-badge">SAXS</span>
<span class="technique-badge">Modelling</span>
</div>
</div>
<!-- Dataset 31: BTK fluorescent probe -->
<div class="dataset-card">
<h3><a href="datasets/dataset-31.html">Fluorescent probe for imaging Bruton's tyrosine kinase</a></h3>
<div class="dataset-meta">
<strong>Organism:</strong> Human BTK<br>
<strong>Years:</strong> ~2023–2024<br>
<strong>Status:</strong> Public
</div>
<div class="dataset-description">
Multimodal characterisation of BTK-targeting fluorescent probe: glycoproteomics/MS, microscopy, NMR.
</div>
<div class="techniques">
<span class="technique-badge">MS / Proteomics</span>
<span class="technique-badge">NMR</span>
<span class="technique-badge">Bioinformatics</span>
</div>
</div>
<!-- Dataset 32: Anaerobic RNR ATP-cone -->
<div class="dataset-card">
<h3><a href="datasets/dataset-32.html">Nucleotide binding to ATP-cone in anaerobic ribonucleotide reductases</a></h3>
<div class="dataset-meta">
<strong>Organism:</strong> Anaerobic RNR (bacterial)<br>
<strong>Years:</strong> ~2024<br>
<strong>Status:</strong> Public
</div>
<div class="dataset-description">
Cryo-EM plus structural proteomics for nucleotide regulation in anaerobic RNRs.
</div>
<div class="techniques">
<span class="technique-badge">Cryo-EM</span>
<span class="technique-badge">MS / Proteomics</span>
</div>
</div>
<!-- Dataset 33: Microsporidian infection apparatus -->
<div class="dataset-card">
<h3><a href="datasets/dataset-33.html">Ultrastructural insights into microsporidian infection apparatus</a></h3>
<div class="dataset-meta">
<strong>Organism:</strong> Microsporidia<br>
<strong>Years:</strong> ~2024<br>
<strong>Status:</strong> Public
</div>
<div class="dataset-description">
Cryo-EM and glycoproteomics of microsporidian infection machinery.
</div>
<div class="techniques">
<span class="technique-badge">Cryo-EM</span>
<span class="technique-badge">MS / Proteomics</span>
</div>
</div>
<!-- Dataset 34: MALT1 allostery -->
<div class="dataset-card">
<h3><a href="datasets/dataset-34.html">MALT1 allostery from NMR and AlphaFold</a></h3>
<div class="dataset-meta">
<strong>Organism:</strong> Human MALT1<br>
<strong>Years:</strong> ~2023–2024<br>
<strong>Status:</strong> Public
</div>
<div class="dataset-description">
NMR and AlphaFold combined for MALT1 allostery and structural dynamics.
</div>
<div class="techniques">
<span class="technique-badge">NMR</span>
<span class="technique-badge">Bioinformatics</span>
<span class="technique-badge">Modelling</span>
</div>
</div>
<!-- Dataset 35: Protein-surfactant complexes -->
<div class="dataset-card">
<h3><a href="datasets/dataset-35.html">Integrative toolbox for protein–surfactant complexes – NMR and SAXS/SANS</a></h3>
<div class="dataset-meta">
<strong>Organism:</strong> Protein–surfactant model systems<br>
<strong>Years:</strong> ~2020<br>
<strong>Status:</strong> Public
</div>
<div class="dataset-description">
NMR, SAXS and SANS for integrative characterisation of protein–surfactant complexes.
</div>
<div class="techniques">
<span class="technique-badge">NMR</span>
<span class="technique-badge">SAXS</span>
<span class="technique-badge">SANS</span>
<span class="technique-badge">Modelling</span>
</div>
</div>
<!-- Dataset 36: Pyridine 2-pyridones amyloid -->
<div class="dataset-card">
<h3><a href="datasets/dataset-36.html">Pyridine-fused 2-pyridones – amyloid fibril binding</a></h3>
<div class="dataset-meta">
<strong>Organism:</strong> Amyloid fibrils (synthetic compounds)<br>
<strong>Years:</strong> ~2018<br>
<strong>Status:</strong> Public
</div>
<div class="dataset-description">
Cryo-EM and NMR for amyloid-binding pyridine-fused 2-pyridones.
</div>
<div class="techniques">
<span class="technique-badge">Cryo-EM</span>
<span class="technique-badge">NMR</span>
<span class="technique-badge">Modelling</span>
</div>
</div>
</div>
</div>
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<p>ISB Dataset Portal | SciLifeLab</p>
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