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<p>This is a data repository for a large study that involved the analysis and prediction of homotypic (self-self) transmembrane domain interactions.</p> <p>Publication: - Yao Xiao, Bo Zeng, Nicola Berner, Dmitrij Frishman, Dieter Langosch, Mark George Teese - Experimental determination and data-driven prediction of homotypic transmembrane domain interfaces - Computational and Structural Biotechnology Journal - Volume 18, 2020, Pages 3230-3242 - ISSN 2001-0370 - <a href="https://doi.org/10.1016/j.csbj.2020.09.035" rel="nofollow">https://doi.org/10.1016/j.csbj.2020.09.035</a></p> <p>Contributors: - Yao Xiao - Bo Zeng - Mark Teese - Dieter Langosch - Dmitrij Frishman</p> <p>Contact:</p> <ul> <li>Mark Teese</li> </ul> <p>Affiliation:</p> <ul> <li><a href="https://www.tum.de/en/" rel="nofollow">Technical University of Munich</a></li> <li><a href="https://www.tngtech.com/en/index.html" rel="nofollow">TNG Technology Consulting GmbH</a></li> </ul> <p>Related website with machine-learning tool: - <a href="http://www.thoipa.org" rel="nofollow">www.thoipa.org</a></p> <p>Related open-source software repositories:</p> <ul> <li><a href="https://github.com/bojigu/thoipapy" rel="nofollow">THOIPApy code repository</a></li> <li><a href="https://bitbucket.org/yaoxiaorepos/datoxr" rel="nofollow">datoxr code repository</a></li> <li><a href="https://github.com/teese/pytoxr" rel="nofollow">pytoxr code repository</a></li> </ul> <p>Open Science Foundation Repository Contents:</p> <ul> <li>data</li> <li>THOIPA_data.7zip<ul> <li>homologues (BLAST data files and alignments)</li> <li>interface_predictions (predictions from THOIPA, PREDDIMER, TMDOCK used for validation)</li> <li>interface_residues (experimental data on TM homodimer interfaces from NMR, ETRA, and crystal structure experiments)</li> <li>residue_properties (data on conservation, polarity, coevolution etc calculated for each residue of each TMD in each dataset)</li> <li>THOIPA_validation (raw validation data (ROC AUC, etc) for the THOIPA machine learning predictor. Also contains the machine-learning model, training_data, and feature importances)</li> </ul> </li> <li>protein_lists<ul> <li>[list of proteins in homotypic TM dataset, and also individual datasets. includes sequences in fastA format]</li> </ul> </li> <li>figures</li> <li>DDR2 results and other scanning mutagenesis data</li> <li>methods</li> <li>hydrophobicity scales and other data related to methods</li> </ul> <p>Data notes:</p> <ul> <li>The following sets of proteins are included in the protein_lists folder</li> <li>set05 : homotypic TMD dataset (combined ETRA, NMR, X-ray)</li> <li>set07 : test data for machine learning</li> <li>set08 : train data for machine learning</li> <li>folders labelled "old, deprecated data" refer to an older machine-learning model, trained on a slightly modified set05.</li> <li>the hierarchical data structure in THOIPA_data.7zip should in most cases be self-explanatory. Also, references and code for the processing of each file can be found in <a href="https://github.com/bojigu/thoipapy" rel="nofollow">thoipapy software</a> version 1.1.3. Most data can be recreated using the open-source thoipapy software.</li> </ul>
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