{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,15]],"date-time":"2026-05-15T08:41:45Z","timestamp":1778834505346,"version":"3.51.4"},"reference-count":20,"publisher":"Oxford University Press (OUP)","issue":"4","license":[{"start":{"date-parts":[[2024,3,21]],"date-time":"2024-03-21T00:00:00Z","timestamp":1710979200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100004727","name":"Flanders Institute for Biotechnology","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100004727","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Fund for Scientific Research Flanders","award":["S000523N"],"award-info":[{"award-number":["S000523N"]}]},{"name":"Fund for Scientific Research Flanders","award":["S000722N"],"award-info":[{"award-number":["S000722N"]}]},{"name":"Spanish Ministry of Science and Innovation through the Centro de Excelencia Severo Ochoa","award":["CEX2020-001049-S"],"award-info":[{"award-number":["CEX2020-001049-S"]}]},{"name":"Spanish Ministry of Science and Innovation through the Centro de Excelencia Severo Ochoa","award":["MCIN\/AEI \/10.13039\/501100011033"],"award-info":[{"award-number":["MCIN\/AEI \/10.13039\/501100011033"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024,3,29]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Motivation<\/jats:title>\n                    <jats:p>Deep learning algorithms applied to structural biology often struggle to converge to meaningful solutions when limited data is available, since they are required to learn complex physical rules from examples. State-of-the-art force-fields, however, cannot interface with deep learning algorithms due to their implementation.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>We present MadraX, a forcefield implemented as a differentiable PyTorch module, able to interact with deep learning algorithms in an end-to-end fashion.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Availability and implementation<\/jats:title>\n                    <jats:p>MadraX documentation, together with tutorials and installation guide, is available at madrax.readthedocs.io.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1093\/bioinformatics\/btae160","type":"journal-article","created":{"date-parts":[[2024,3,19]],"date-time":"2024-03-19T11:34:55Z","timestamp":1710848095000},"source":"Crossref","is-referenced-by-count":6,"title":["Integrating physics in deep learning algorithms: a force field as a PyTorch module"],"prefix":"10.1093","volume":"40","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5935-5258","authenticated-orcid":false,"given":"Gabriele","family":"Orlando","sequence":"first","affiliation":[{"name":"Switch Laboratory, VIB Center for Brain and Disease Research, VIB , Leuven 3000, Belgium"},{"name":"Switch Laboratory, Department of Cellular and Molecular Medicine, KU Leuven , Leuven 3000, Belgium"},{"name":"Switch Laboratory, VIB Center for AI & Computational Biology, VIB , Leuven 3000, Belgium"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5276-1392","authenticated-orcid":false,"given":"Luis","family":"Serrano","sequence":"additional","affiliation":[{"name":"Centre for Genomic Regulation (CRG), The Barcelona Institute for Science and Technology , Dr Aiguader 88 , Barcelona 08003, Spain"},{"name":"Universitat Pompeu Fabra (UPF) , Barcelona, Spain"},{"name":"IC REA, Pg. 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