{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,15]],"date-time":"2026-09-15T10:42:21Z","timestamp":1789468941241,"version":"build-2803163510"},"reference-count":32,"publisher":"Wiley","license":[{"start":{"date-parts":[[2026,8,29]],"date-time":"2026-08-29T00:00:00Z","timestamp":1787961600000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2026,8,29]],"date-time":"2026-08-29T00:00:00Z","timestamp":1787961600000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"funder":[{"DOI":"10.13039\/501100011787","name":"Heilongjiang Provincial Science and Technology Department","doi-asserted-by":"publisher","award":["2022ZX103C01"],"award-info":[{"award-number":["2022ZX103C01"]}],"id":[{"id":"10.13039\/501100011787","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100002855","name":"Ministry of Science and Technology of the People's Republic of China","doi-asserted-by":"publisher","award":["2025ZD0215700"],"award-info":[{"award-number":["2025ZD0215700"]}],"id":[{"id":"10.13039\/501100002855","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["advanced.onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Advanced Science"],"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:p>\n                    Predicting how single cells respond to perturbations is a central problem in computational biology, with potential relevance to emerging artificial intelligence virtual cell (AIVC) research and drug\u2010discovery efforts. However, substantial variation in perturbation responses across biological contexts and the limited generalizability of current models make prediction across cell types, patients, species, and other contexts particularly challenging. To address this challenge, we present single\u2010cell perturbation inference via latent optimal transport (scPILOT), a query\u2010conditioned framework for transferring responses to previously observed perturbations across biological contexts. scPILOT learns a generative latent representation through discriminator\u2010assisted training and separates perturbation inference into cell\u2010level response estimation from observed contexts and query\u2010specific response transfer using latent optimal transport. Across held\u2010out cell\u2010type, patient, and species benchmarks, scPILOT achieved context\u2010averaged\n                    <jats:italic>R<\/jats:italic>\n                    <jats:sup>2<\/jats:sup>\n                    <jats:sub>mean<\/jats:sub>\n                    \/MMD\n                    <jats:sup>2<\/jats:sup>\n                    values of 0.945\/0.137, 0.598\/0.025, and 0.853\/0.287, respectively. It also maintained strong population\u2010average accuracy in a held\u2010out cell\u2010line benchmark, while complementary analyses indicated that performance was associated with dataset learnability and query\u2013context match. With the continued expansion of single\u2010cell perturbation datasets, scPILOT may provide a practical framework for transferring responses to previously observed perturbations across increasingly diverse biological contexts.\n                  <\/jats:p>","DOI":"10.1002\/advs.77461","type":"journal-article","created":{"date-parts":[[2026,8,29]],"date-time":"2026-08-29T09:28:47Z","timestamp":1787995727000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Predicting Single\u2010Cell Perturbation Responses Across Biological Contexts With a Deep Generative Model Integrating Optimal Transport"],"prefix":"10.1002","author":[{"given":"Jialiang","family":"Wang","sequence":"first","affiliation":[{"name":"School of Computer Science and Technology Harbin Institute of Technology  Harbin China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ziqi","family":"Liu","sequence":"additional","affiliation":[{"name":"School of Computer Science and Technology Harbin Institute of Technology  Harbin China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhengqian","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Computer Science and Technology Harbin Institute of Technology  Harbin China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yikun","family":"Cao","sequence":"additional","affiliation":[{"name":"School of Computer Science and Technology Harbin Institute of Technology  Harbin China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Junjun","family":"Ren","sequence":"additional","affiliation":[{"name":"School of Computer Science and Technology Harbin Institute of Technology  Harbin China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Peng","family":"Cheng","sequence":"additional","affiliation":[{"name":"HIT\u2010HULU Joint Institute of Industrial Technology in Precision Medicine  Harbin China"},{"name":"Genvista Technology Co., Ltd.  Harbin China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jingjing","family":"Tian","sequence":"additional","affiliation":[{"name":"HIT\u2010HULU Joint Institute of Industrial Technology in Precision Medicine  Harbin China"},{"name":"Genvista Technology Co., Ltd.  Harbin China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lingyun","family":"Xie","sequence":"additional","affiliation":[{"name":"School of Computer Science and Technology Harbin Institute of Technology  Harbin China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xin","family":"Lu","sequence":"additional","affiliation":[{"name":"College of Systems Engineering National University of Defense Technology  Changsha China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2020-767X","authenticated-orcid":false,"given":"Zhanwei","family":"Du","sequence":"additional","affiliation":[{"name":"School of Public Health and Emergency Management Southern University of Science and Technology  Shenzhen China"},{"name":"WHO Collaborating Centre for Infectious Disease Epidemiology and Control School of Public Health Li Ka Shing Faculty of Medicine The University of Hong Kong  Hong Kong SAR China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2572-7420","authenticated-orcid":false,"given":"Yongzhuang","family":"Liu","sequence":"additional","affiliation":[{"name":"School of Computer Science and Technology Harbin Institute of Technology  Harbin China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2026,8,29]]},"reference":[{"key":"e_1_2_10_2_1","doi-asserted-by":"publisher","DOI":"10.1038\/nrg3542"},{"key":"e_1_2_10_3_1","doi-asserted-by":"publisher","DOI":"10.1186\/s13073\u2010017\u20100467\u20104"},{"key":"e_1_2_10_4_1","doi-asserted-by":"publisher","DOI":"10.1038\/s12276\u2010018\u20100071\u20108"},{"key":"e_1_2_10_5_1","doi-asserted-by":"crossref","unstructured":"L.Hetzel S.B\u00f6hm N.Kilbertus S.G\u00fcnnemann M.Lotfollahi andF.Theis \u201cPredicting Cellular Responses to Novel Drug Perturbations at a Single\u2010Cell Resolution \u201d inProceedings of the 36th 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