{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,29]],"date-time":"2026-09-29T04:55:47Z","timestamp":1790657747753,"version":"4.1.0"},"reference-count":270,"publisher":"Elsevier BV","issue":"19","license":[{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,8,19]],"date-time":"2026-08-19T00:00:00Z","timestamp":1787097600000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100003187","name":"NSF","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100003187","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000865","name":"Gates Foundation","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100000865","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100014989","name":"Chan Zuckerberg Initiative","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100014989","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100018231","name":"Aligning Science Across Parkinson's","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100018231","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100000289","name":"Cancer Research UK","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100000289","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["cell.com","elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Cell"],"published-print":{"date-parts":[[2026,9]]},"DOI":"10.1016\/j.cell.2026.08.032","type":"journal-article","created":{"date-parts":[[2026,9,17]],"date-time":"2026-09-17T15:09:26Z","timestamp":1789657766000},"page":"5845-5869","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":1,"title":["World models for biomedicine"],"prefix":"10.1016","volume":"189","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1420-1236","authenticated-orcid":false,"given":"Ayush","family":"Noori","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nic","family":"Fishman","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ada","family":"Fang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lukas","family":"Fesser","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8530-7228","authenticated-orcid":false,"given":"Marinka","family":"Zitnik","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"key":"10.1016\/j.cell.2026.08.032_bib1","unstructured":"Bernard, C. (1865). Introduction \u00e0 l\u2019\u00c9tude de la M\u00e9decine Exp\u00e9rimentale (J.-B. Bailli\u00e8re et Fils)."},{"key":"10.1016\/j.cell.2026.08.032_bib2","series-title":"An Introduction to the Study of Experimental Medicine","author":"Bernard","year":"1927"},{"key":"10.1016\/j.cell.2026.08.032_bib3","doi-asserted-by":"crossref","first-page":"402","DOI":"10.1038\/s41586-020-2188-x","article-title":"A reference map of the human binary protein interactome","volume":"580","author":"Luck","year":"2020","journal-title":"Nature"},{"key":"10.1016\/j.cell.2026.08.032_bib4","doi-asserted-by":"crossref","DOI":"10.1126\/science.abn8197","article-title":"The landscape of tolerated genetic variation in humans and primates","volume":"380","author":"Gao","year":"2023","journal-title":"Science"},{"key":"10.1016\/j.cell.2026.08.032_bib5","doi-asserted-by":"crossref","first-page":"3736","DOI":"10.1016\/j.cell.2026.03.044","article-title":"Global genetic interaction network of a human cell maps conserved principles and informs functional interpretation of gene co-essentiality profiles","volume":"189","author":"Billmann","year":"2026","journal-title":"Cell"},{"key":"10.1016\/j.cell.2026.08.032_bib6","doi-asserted-by":"crossref","DOI":"10.1126\/scitranslmed.aag1166","article-title":"The druggable genome and support for target identification and validation in drug development","volume":"9","author":"Finan","year":"2017","journal-title":"Sci. Transl. Med."},{"key":"10.1016\/j.cell.2026.08.032_bib7","doi-asserted-by":"crossref","DOI":"10.1371\/journal.pbio.2006643","article-title":"Large-scale investigation of the reasons why potentially important genes are ignored","volume":"16","author":"Stoeger","year":"2018","journal-title":"PLOS Biol."},{"key":"10.1016\/j.cell.2026.08.032_bib8","doi-asserted-by":"crossref","first-page":"317","DOI":"10.1038\/nrd.2018.14","article-title":"Unexplored therapeutic opportunities in the human genome","volume":"17","author":"Oprea","year":"2018","journal-title":"Nat. Rev. Drug Discov."},{"key":"10.1016\/j.cell.2026.08.032_bib10","doi-asserted-by":"crossref","first-page":"647","DOI":"10.1038\/s41586-025-08744-2","article-title":"Mastering diverse control tasks through world models","volume":"640","author":"Hafner","year":"2025","journal-title":"Nature"},{"key":"10.1016\/j.cell.2026.08.032_bib9","article-title":"World Models","author":"Ha","year":"2018","journal-title":"arXiv"},{"key":"10.1016\/j.cell.2026.08.032_bib11","article-title":"Cosmos World Foundation Model Platform for Physical AI","author":"Agarwal","year":"2025","journal-title":"arXiv"},{"key":"10.1016\/j.cell.2026.08.032_bib12","article-title":"V-JEPA 2: Self-Supervised Video Models Enable Understanding, Prediction and Planning","author":"Assran","year":"2025","journal-title":"arXiv"},{"key":"10.1016\/j.cell.2026.08.032_bib13","article-title":"GAIA-1: a Generative World Model for Autonomous Driving","author":"Hu","year":"2023","journal-title":"arXiv"},{"key":"10.1016\/j.cell.2026.08.032_bib14","doi-asserted-by":"crossref","first-page":"6125","DOI":"10.1016\/j.cell.2024.09.022","article-title":"Empowering biomedical discovery with AI agents","volume":"187","author":"Gao","year":"2024","journal-title":"Cell"},{"key":"10.1016\/j.cell.2026.08.032_bib15","article-title":"Language Agents Achieve Superhuman Synthesis of Scientific Knowledge","author":"Skarlinski","year":"2024","journal-title":"arXiv"},{"key":"10.1016\/j.cell.2026.08.032_bib16","article-title":"Kosmos: an AI Scientist for Autonomous Discovery","author":"Mitchener","year":"2025","journal-title":"arXiv"},{"key":"10.1016\/j.cell.2026.08.032_bib17","doi-asserted-by":"crossref","first-page":"487","DOI":"10.1038\/s41586-026-10644-y","article-title":"Accelerating scientific discovery with Co-Scientist","volume":"655","author":"Gottweis","year":"2026","journal-title":"Nature"},{"key":"10.1016\/j.cell.2026.08.032_bib18","doi-asserted-by":"crossref","first-page":"497","DOI":"10.1038\/s41586-026-10652-y","article-title":"A multi-agent system for automating scientific discovery","volume":"655","author":"Ghareeb","year":"2026","journal-title":"Nature"},{"key":"10.1016\/j.cell.2026.08.032_bib19","doi-asserted-by":"crossref","first-page":"86","DOI":"10.1038\/s41586-023-06734-w","article-title":"An autonomous laboratory for the accelerated synthesis of inorganic materials","volume":"624","author":"Szymanski","year":"2023","journal-title":"Nature"},{"key":"10.1016\/j.cell.2026.08.032_bib20","doi-asserted-by":"crossref","first-page":"570","DOI":"10.1038\/s41586-023-06792-0","article-title":"Autonomous chemical research with large language models","volume":"624","author":"Boiko","year":"2023","journal-title":"Nature"},{"key":"10.1016\/j.cell.2026.08.032_bib21","doi-asserted-by":"crossref","first-page":"97","DOI":"10.1038\/s44286-023-00002-4","article-title":"Self-driving laboratories to autonomously navigate the protein fitness landscape","volume":"1","author":"Rapp","year":"2024","journal-title":"Nat Chem Eng."},{"key":"10.1016\/j.cell.2026.08.032_bib22","doi-asserted-by":"crossref","DOI":"10.1038\/s41467-025-61209-y","article-title":"A generalized platform for artificial intelligence-powered autonomous enzyme engineering","volume":"16","author":"Singh","year":"2025","journal-title":"Nat. Commun."},{"key":"10.1016\/j.cell.2026.08.032_bib23","doi-asserted-by":"crossref","first-page":"2190","DOI":"10.1016\/j.ajhg.2024.08.010","article-title":"Assessing the utility of large language models for phenotype-driven gene prioritization in the diagnosis of rare genetic disease","volume":"111","author":"Kim","year":"2024","journal-title":"Am. J. Hum. Genet."},{"key":"10.1016\/j.cell.2026.08.032_bib24","article-title":"Survey and improvement strategies for gene prioritization with large language models","volume":"5","author":"Neeley","year":"2025","journal-title":"Bioinform. Adv."},{"key":"10.1016\/j.cell.2026.08.032_bib25","series-title":"The Nature of Explanation","author":"Craik","year":"1952"},{"key":"10.1016\/j.cell.2026.08.032_bib26","doi-asserted-by":"crossref","first-page":"151","DOI":"10.1037\/h0048495","article-title":"Elements of a theory of human problem solving","volume":"65","author":"Newell","year":"1958","journal-title":"Psychol. Rev."},{"key":"10.1016\/j.cell.2026.08.032_bib27","unstructured":"Minsky, M. (1965) Matter, Mind and Models."},{"key":"10.1016\/j.cell.2026.08.032_bib28","series-title":"Readings in Artificial Intelligence","first-page":"431","article-title":"Some Philosophical Problems from the Standpoint of Artificial Intelligence","author":"McCarthy","year":"1981"},{"key":"10.1016\/j.cell.2026.08.032_bib29","doi-asserted-by":"crossref","first-page":"189","DOI":"10.1016\/0004-3702(71)90010-5","article-title":"STRIPS: A new approach to the application of theorem proving to problem solving","volume":"2","author":"Fikes","year":"1971","journal-title":"Artif. Intell."},{"key":"10.1016\/j.cell.2026.08.032_bib30","first-page":"217","article-title":"An adaptive network that constructs and uses and internal model of its world","volume":"4","author":"Sutton","year":"1981","journal-title":"Cognition and Brain Theory"},{"key":"10.1016\/j.cell.2026.08.032_bib31","article-title":"The Learning of World Models By Connectionist Networks","volume":"7","author":"Sutton","year":"1985","journal-title":"Proceedings of the Annual Meeting of the Cognitive Science Society"},{"key":"10.1016\/j.cell.2026.08.032_bib32","series-title":"Machine Learning Proceedings 1990","first-page":"216","article-title":"Integrated Architectures for Learning, Planning, and Reacting Based on Approximating Dynamic Programming","author":"Sutton","year":"1990"},{"key":"10.1016\/j.cell.2026.08.032_bib33","series-title":"Making the World Differentiable: on Using Self Supervised Fully Recurrent Neural Networks for Dynamic Reinforcement Learning and Planning in Non-stationary Environments","author":"Schmidhuber","year":"1990"},{"key":"10.1016\/j.cell.2026.08.032_bib34","series-title":"From Animals to Animats, Proceedings of the First International Conference on Simulation of Adaptive Behavior","first-page":"222","article-title":"A Possibility for Implementing Curiosity and Boredom in Model-Building Neural Controllers","author":"Schmidhuber","year":"1991"},{"key":"10.1016\/j.cell.2026.08.032_bib35","doi-asserted-by":"crossref","first-page":"293","DOI":"10.1023\/A:1022628806385","article-title":"Self-improving reactive agents based on reinforcement learning, planning and teaching","volume":"8","author":"Lin","year":"1992","journal-title":"Mach. Learn."},{"key":"10.1016\/j.cell.2026.08.032_bib36","doi-asserted-by":"crossref","first-page":"237","DOI":"10.1613\/jair.301","article-title":"Reinforcement Learning: A Survey","volume":"4","author":"Kaelbling","year":"1996","journal-title":"J. Artif. Intell. Res."},{"key":"10.1016\/j.cell.2026.08.032_bib37","first-page":"1","article-title":"A path towards autonomous machine intelligence","volume":"62","author":"LeCun","year":"2022","journal-title":"Open Rev."},{"key":"10.1016\/j.cell.2026.08.032_bib38","article-title":"Reasoning with Language Model is Planning with World Model","author":"Hao","year":"2023","journal-title":"arXiv"},{"key":"10.1016\/j.cell.2026.08.032_bib39","article-title":"Genie: Generative Interactive Environments","author":"Bruce","year":"2024","journal-title":"arXiv"},{"key":"10.1016\/j.cell.2026.08.032_bib40","article-title":"Emergent World Representations: Exploring a Sequence Model Trained on a Synthetic Task","author":"Li","year":"2024","journal-title":"arXiv"},{"key":"10.1016\/j.cell.2026.08.032_bib41","article-title":"Evaluating the World Model Implicit in a Generative Model","author":"Vafa","year":"2024","journal-title":"arXiv"},{"key":"10.1016\/j.cell.2026.08.032_bib42","article-title":"On the Opportunities and Risks of Foundation Models","author":"Bommasani","year":"2022","journal-title":"arXiv"},{"key":"10.1016\/j.cell.2026.08.032_bib43","doi-asserted-by":"crossref","first-page":"1263","DOI":"10.1038\/s41587-026-03135-y","article-title":"Tracing the rise of biomedical foundation models","volume":"44","author":"Chang","year":"2026","journal-title":"Nat. Biotechnol."},{"key":"10.1016\/j.cell.2026.08.032_bib44","doi-asserted-by":"crossref","first-page":"1206","DOI":"10.1038\/s41586-025-10014-0","article-title":"Advancing regulatory variant effect prediction with AlphaGenome","volume":"649","author":"Avsec","year":"2026","journal-title":"Nature"},{"key":"10.1016\/j.cell.2026.08.032_bib45","doi-asserted-by":"crossref","DOI":"10.1126\/science.ado9336","article-title":"Sequence modeling and design from molecular to genome scale with Evo","volume":"386","author":"Nguyen","year":"2024","journal-title":"Science"},{"key":"10.1016\/j.cell.2026.08.032_bib46","doi-asserted-by":"crossref","first-page":"1349","DOI":"10.1038\/s41586-026-10176-5","article-title":"Genome modelling and design across all domains of life with Evo 2","volume":"652","author":"Brixi","year":"2026","journal-title":"Nature"},{"key":"10.1016\/j.cell.2026.08.032_bib47","doi-asserted-by":"crossref","first-page":"287","DOI":"10.1038\/s41592-024-02523-z","article-title":"Nucleotide Transformer: building and evaluating robust foundation models for human genomics","volume":"22","author":"Dalla-Torre","year":"2025","journal-title":"Nat. Methods"},{"key":"10.1016\/j.cell.2026.08.032_bib48","doi-asserted-by":"crossref","first-page":"850","DOI":"10.1126\/science.ads0018","article-title":"Simulating 500 million years of evolution with a language model","volume":"387","author":"Hayes","year":"2025","journal-title":"Science"},{"key":"10.1016\/j.cell.2026.08.032_bib49","article-title":"Language Modeling Materializes a World Model of Protein Biology","author":"Candido","year":"2026","journal-title":"bioRxiv"},{"key":"10.1016\/j.cell.2026.08.032_bib50","doi-asserted-by":"crossref","first-page":"1310","DOI":"10.1038\/s41587-025-02836-0","article-title":"A trimodal protein language model enables advanced protein searches","volume":"44","author":"Su","year":"2025","journal-title":"Nat. Biotechnol."},{"key":"10.1016\/j.cell.2026.08.032_bib51","doi-asserted-by":"crossref","unstructured":"Zhou, G., Gao, Z., Ding, Q., Zheng, H., Xu, H., Wei, Z., Zhang, L., and Ke, G. (2022). Uni-Mol: A Universal 3D Molecular Representation Learning Framework. In.","DOI":"10.26434\/chemrxiv-2022-jjm0j"},{"key":"10.1016\/j.cell.2026.08.032_bib52","article-title":"Learning Universal Representations of Intermolecular Interactions with ATOMICA","author":"Fang","year":"2025","journal-title":"bioRxiv"},{"key":"10.1016\/j.cell.2026.08.032_bib53","doi-asserted-by":"crossref","first-page":"616","DOI":"10.1038\/s41586-023-06139-9","article-title":"Transfer learning enables predictions in network biology","volume":"618","author":"Theodoris","year":"2023","journal-title":"Nature"},{"key":"10.1016\/j.cell.2026.08.032_bib54","doi-asserted-by":"crossref","first-page":"1470","DOI":"10.1038\/s41592-024-02201-0","article-title":"scGPT: toward building a foundation model for single-cell multi-omics using generative AI","volume":"21","author":"Cui","year":"2024","journal-title":"Nat. Methods"},{"key":"10.1016\/j.cell.2026.08.032_bib55","doi-asserted-by":"crossref","first-page":"183","DOI":"10.1038\/s41586-026-10689-z","article-title":"Universal cell embedding provides a foundation model for cell biology","volume":"656","author":"Rosen","year":"2026","journal-title":"Nature"},{"key":"10.1016\/j.cell.2026.08.032_bib56","doi-asserted-by":"crossref","first-page":"850","DOI":"10.1038\/s41591-024-02857-3","article-title":"Towards a general-purpose foundation model for computational pathology","volume":"30","author":"Chen","year":"2024","journal-title":"Nat. Med."},{"key":"10.1016\/j.cell.2026.08.032_bib57","doi-asserted-by":"crossref","first-page":"863","DOI":"10.1038\/s41591-024-02856-4","article-title":"A visual-language foundation model for computational pathology","volume":"30","author":"Lu","year":"2024","journal-title":"Nat. Med."},{"key":"10.1016\/j.cell.2026.08.032_bib58","doi-asserted-by":"crossref","first-page":"181","DOI":"10.1038\/s41586-024-07441-w","article-title":"A whole-slide foundation model for digital pathology from real-world data","volume":"630","author":"Xu","year":"2024","journal-title":"Nature"},{"key":"10.1016\/j.cell.2026.08.032_bib59","first-page":"1","article-title":"The Virtual Tissues foundation model resolves spatial proteomics across scales","author":"Wenckstern","year":"2026","journal-title":"Nature"},{"key":"10.1016\/j.cell.2026.08.032_bib60","article-title":"Multi-scale modeling of human tissues from spatial transcriptomics with TERRA","author":"Birk","year":"2026","journal-title":"bioRxiv"},{"key":"10.1016\/j.cell.2026.08.032_bib61","doi-asserted-by":"crossref","first-page":"3010","DOI":"10.1038\/s41591-026-04502-7","article-title":"Generalizable AI predicts immunotherapy outcomes across cancers and treatments","volume":"32","author":"Shen","year":"2026","journal-title":"Nat. Med."},{"key":"10.1016\/j.cell.2026.08.032_bib62","article-title":"PULSAR: a Foundation Model for Multi-scale and Multicellular Biology","author":"Pang","year":"2025","journal-title":"bioRxiv"},{"key":"10.1016\/j.cell.2026.08.032_bib63","doi-asserted-by":"crossref","first-page":"389","DOI":"10.1016\/j.cell.2012.05.044","article-title":"A Whole-Cell Computational Model Predicts Phenotype from Genotype","volume":"150","author":"Karr","year":"2012","journal-title":"Cell"},{"key":"10.1016\/j.cell.2026.08.032_bib64","doi-asserted-by":"crossref","first-page":"2582","DOI":"10.1016\/j.cell.2026.02.009","article-title":"Bringing the genetically minimal cell to life on a computer in 4D","volume":"189","author":"Thornburg","year":"2026","journal-title":"Cell"},{"key":"10.1016\/j.cell.2026.08.032_bib65","article-title":"Agent Harness for Large Language Model Agents: A Survey","author":"Meng","year":"2026","journal-title":"Preprints"},{"key":"10.1016\/j.cell.2026.08.032_bib66","series-title":"Proceedings of the 36th Annual ACM Symposium on User Interface Software and Technology UIST \u201923","first-page":"1","article-title":"Generative Agents: Interactive Simulacra of Human Behavior","author":"Park","year":"2023"},{"key":"10.1016\/j.cell.2026.08.032_bib67","doi-asserted-by":"crossref","first-page":"1282","DOI":"10.1038\/s41586-026-10675-5","article-title":"Towards autonomous medical artificial intelligence agents","volume":"655","author":"Ferber","year":"2026","journal-title":"Nature"},{"key":"10.1016\/j.cell.2026.08.032_bib68","doi-asserted-by":"crossref","first-page":"442","DOI":"10.1038\/s41586-025-08866-7","article-title":"Towards conversational diagnostic artificial intelligence","volume":"642","author":"Tu","year":"2025","journal-title":"Nature"},{"key":"10.1016\/j.cell.2026.08.032_bib69","doi-asserted-by":"crossref","first-page":"1726","DOI":"10.1038\/s41591-026-04371-0","article-title":"Advancing conversational diagnostic AI with multimodal reasoning","volume":"32","author":"Saab","year":"2026","journal-title":"Nat. Med."},{"key":"10.1016\/j.cell.2026.08.032_bib70","article-title":"LabOS: the AI-XR Co-scientist That Sees and Works With Humans","author":"Cong","year":"2025","journal-title":"arXiv"},{"key":"10.1016\/j.cell.2026.08.032_bib71","doi-asserted-by":"crossref","DOI":"10.1073\/pnas.2532645122","article-title":"Digital twins come to the life sciences","volume":"122","author":"Adam","year":"2025","journal-title":"Proc. Natl. Acad. Sci. USA"},{"key":"10.1016\/j.cell.2026.08.032_bib72","doi-asserted-by":"crossref","first-page":"2559","DOI":"10.1016\/j.cell.2022.05.013","article-title":"Mapping information-rich genotype-phenotype landscapes with genome-scale Perturb-seq","volume":"185","author":"Replogle","year":"2022","journal-title":"Cell"},{"key":"10.1016\/j.cell.2026.08.032_bib73","article-title":"Tahoe-100M: A Giga-Scale Single-Cell Perturbation Atlas for Context-Dependent Gene Function and Cellular Modeling","author":"Zhang","year":"2025","journal-title":"bioRxiv"},{"key":"10.1016\/j.cell.2026.08.032_bib74","doi-asserted-by":"crossref","first-page":"1437","DOI":"10.1016\/j.cell.2017.10.049","article-title":"A Next Generation Connectivity Map: L1000 Platform and the First 1,000,000 Profiles","volume":"171","author":"Subramanian","year":"2017","journal-title":"Cell"},{"key":"10.1016\/j.cell.2026.08.032_bib75","doi-asserted-by":"crossref","first-page":"1084","DOI":"10.1038\/s41586-024-07069-w","article-title":"A single-cell time-lapse of mouse prenatal development from gastrula to birth","volume":"626","author":"Qiu","year":"2024","journal-title":"Nature"},{"key":"10.1016\/j.cell.2026.08.032_bib76","doi-asserted-by":"crossref","first-page":"751","DOI":"10.1038\/s41586-026-10545-0","article-title":"Spatiotemporal transcriptome atlas of human embryos after gastrulation","volume":"654","author":"Pan","year":"2026","journal-title":"Nature"},{"key":"10.1016\/j.cell.2026.08.032_bib77","doi-asserted-by":"crossref","first-page":"E2467","DOI":"10.1073\/pnas.1714723115","article-title":"Fundamental limits on dynamic inference from single-cell snapshots","volume":"115","author":"Weinreb","year":"2018","journal-title":"Proc. Natl. Acad. Sci. USA"},{"key":"10.1016\/j.cell.2026.08.032_bib78","doi-asserted-by":"crossref","first-page":"248","DOI":"10.1038\/s41586-025-09529-3","article-title":"Learning the natural history of human disease with generative transformers","volume":"647","author":"Shmatko","year":"2025","journal-title":"Nature"},{"key":"10.1016\/j.cell.2026.08.032_bib79","article-title":"MediSim: Multi-granular simulation for enriching longitudinal, multi-modal electronic health records","volume":"6","author":"Theodorou","year":"2025","journal-title":"Patterns (N Y)"},{"key":"10.1016\/j.cell.2026.08.032_bib80","doi-asserted-by":"crossref","DOI":"10.1038\/s41467-024-51795-8","article-title":"Uncovering the heritable components of multimorbidities and disease trajectories using a nationwide cohort","volume":"15","author":"Westergaard","year":"2024","journal-title":"Nat. Commun."},{"key":"10.1016\/j.cell.2026.08.032_bib81","doi-asserted-by":"crossref","first-page":"7045","DOI":"10.1016\/j.cell.2024.11.015","article-title":"How to build the virtual cell with artificial intelligence: Priorities and opportunities","volume":"187","author":"Bunne","year":"2024","journal-title":"Cell"},{"key":"10.1016\/j.cell.2026.08.032_bib82","doi-asserted-by":"crossref","first-page":"927","DOI":"10.1038\/s41587-023-01905-6","article-title":"Predicting transcriptional outcomes of novel multigene perturbations with GEARS","volume":"42","author":"Roohani","year":"2024","journal-title":"Nat. Biotechnol."},{"key":"10.1016\/j.cell.2026.08.032_bib83","article-title":"CellFlow enables generative single-cell phenotype modeling with flow matching","author":"Klein","year":"2025","journal-title":"bioRxiv"},{"key":"10.1016\/j.cell.2026.08.032_bib84","article-title":"Predicting cellular responses to perturbation across diverse contexts with State","author":"Adduri","year":"2025","journal-title":"bioRxiv"},{"key":"10.1016\/j.cell.2026.08.032_bib85","first-page":"1","article-title":"TxPert: using multiple knowledge graphs for prediction of transcriptomic perturbation effects","author":"Wenkel","year":"2026","journal-title":"Nat. Biotechnol."},{"key":"10.1016\/j.cell.2026.08.032_bib86","article-title":"Stack: In-Context Learning of Single-Cell Biology","author":"Dong","year":"2026","journal-title":"bioRxiv"},{"key":"10.1016\/j.cell.2026.08.032_bib87","article-title":"X-Cell: Scaling Causal Perturbation Prediction Across Diverse Cellular Contexts via Diffusion Language Models","author":"Wang","year":"2026","journal-title":"bioRxiv"},{"key":"10.1016\/j.cell.2026.08.032_bib88","article-title":"MORPH Predicts the Single-Cell Outcome of Genetic Perturbations Across Conditions and Data Modalities","author":"He","year":"2025","journal-title":"bioRxiv"},{"key":"10.1016\/j.cell.2026.08.032_bib89","doi-asserted-by":"crossref","first-page":"1657","DOI":"10.1038\/s41592-025-02772-6","article-title":"Deep-learning-based gene perturbation effect prediction does not yet outperform simple linear baselines","volume":"22","author":"Ahlmann-Eltze","year":"2025","journal-title":"Nat. Methods"},{"key":"10.1016\/j.cell.2026.08.032_bib90","doi-asserted-by":"crossref","DOI":"10.1186\/s13059-025-03840-y","article-title":"A comparison of computational methods for expression forecasting","volume":"26","author":"Kernfeld","year":"2025","journal-title":"Genome Biol."},{"key":"10.1016\/j.cell.2026.08.032_bib91","doi-asserted-by":"crossref","DOI":"10.1093\/bioinformatics\/btaf317","article-title":"Simple controls exceed best deep learning algorithms and reveal foundation model effectiveness for predicting genetic perturbations","volume":"41","author":"Wong","year":"2025","journal-title":"Bioinformatics"},{"key":"10.1016\/j.cell.2026.08.032_bib92","doi-asserted-by":"crossref","first-page":"1050","DOI":"10.1038\/s41587-025-02777-8","article-title":"Systema: a framework for evaluating genetic perturbation response prediction beyond systematic variation","volume":"44","author":"Vi\u00f1as Torn\u00e9","year":"2026","journal-title":"Nat. Biotechnol."},{"key":"10.1016\/j.cell.2026.08.032_bib93","doi-asserted-by":"crossref","first-page":"451","DOI":"10.1038\/s41592-025-02980-0","article-title":"Benchmarking algorithms for generalizable single-cell perturbation response prediction","volume":"23","author":"Wei","year":"2026","journal-title":"Nat. Methods"},{"key":"10.1016\/j.cell.2026.08.032_bib94","article-title":"Virtual Cells Need Context, Not Just Scale","author":"Dibaeinia","year":"2026","journal-title":"bioRxiv"},{"key":"10.1016\/j.cell.2026.08.032_bib95","doi-asserted-by":"crossref","first-page":"1228","DOI":"10.1038\/s41588-025-02169-3","article-title":"Transcriptome-wide analysis of differential expression in perturbation atlases","volume":"57","author":"Nadig","year":"2025","journal-title":"Nat. Genet."},{"key":"10.1016\/j.cell.2026.08.032_bib96","first-page":"1","article-title":"Towards predictive virtual embryos with genomics and AI","author":"Cao","year":"2026","journal-title":"Nat. Methods"},{"key":"10.1016\/j.cell.2026.08.032_bib97","doi-asserted-by":"crossref","first-page":"490","DOI":"10.1038\/s41586-019-0933-9","article-title":"A single-cell molecular map of mouse gastrulation and early organogenesis","volume":"566","author":"Pijuan-Sala","year":"2019","journal-title":"Nature"},{"key":"10.1016\/j.cell.2026.08.032_bib98","doi-asserted-by":"crossref","first-page":"487","DOI":"10.1038\/s41586-019-1825-8","article-title":"Multi-omics profiling of mouse gastrulation at single-cell resolution","volume":"576","author":"Argelaguet","year":"2019","journal-title":"Nature"},{"key":"10.1016\/j.cell.2026.08.032_bib99","doi-asserted-by":"crossref","first-page":"604","DOI":"10.1038\/s41556-023-01108-w","article-title":"A single-cell transcriptome atlas profiles early organogenesis in human embryos","volume":"25","author":"Xu","year":"2023","journal-title":"Nat. Cell Biol."},{"key":"10.1016\/j.cell.2026.08.032_bib100","doi-asserted-by":"crossref","first-page":"772","DOI":"10.1038\/s41586-023-06548-w","article-title":"Single-cell, whole-embryo phenotyping of mammalian developmental disorders","volume":"623","author":"Huang","year":"2023","journal-title":"Nature"},{"key":"10.1016\/j.cell.2026.08.032_bib101","doi-asserted-by":"crossref","first-page":"782","DOI":"10.1038\/s41586-023-06720-2","article-title":"Embryo-scale reverse genetics at single-cell resolution","volume":"623","author":"Saunders","year":"2023","journal-title":"Nature"},{"key":"10.1016\/j.cell.2026.08.032_bib102","doi-asserted-by":"crossref","DOI":"10.1038\/s41467-026-70989-w","article-title":"MIC-Drop-seq: scalable single-cell phenotyping of mutant vertebrate embryos","volume":"17","author":"Carey","year":"2026","journal-title":"Nat. Commun."},{"key":"10.1016\/j.cell.2026.08.032_bib103","doi-asserted-by":"crossref","first-page":"381","DOI":"10.1038\/nbt.2859","article-title":"The dynamics and regulators of cell fate decisions are revealed by pseudotemporal ordering of single cells","volume":"32","author":"Trapnell","year":"2014","journal-title":"Nat. Biotechnol."},{"key":"10.1016\/j.cell.2026.08.032_bib104","doi-asserted-by":"crossref","first-page":"979","DOI":"10.1038\/nmeth.4402","article-title":"Reversed graph embedding resolves complex single-cell trajectories","volume":"14","author":"Qiu","year":"2017","journal-title":"Nat. Methods"},{"key":"10.1016\/j.cell.2026.08.032_bib105","doi-asserted-by":"crossref","first-page":"451","DOI":"10.1038\/s41587-019-0068-4","article-title":"Characterization of cell fate probabilities in single-cell data with Palantir","volume":"37","author":"Setty","year":"2019","journal-title":"Nat. Biotechnol."},{"key":"10.1016\/j.cell.2026.08.032_bib106","doi-asserted-by":"crossref","first-page":"494","DOI":"10.1038\/s41586-018-0414-6","article-title":"RNA velocity of single cells","volume":"560","author":"La Manno","year":"2018","journal-title":"Nature"},{"key":"10.1016\/j.cell.2026.08.032_bib107","doi-asserted-by":"crossref","first-page":"1408","DOI":"10.1038\/s41587-020-0591-3","article-title":"Generalizing RNA velocity to transient cell states through dynamical modeling","volume":"38","author":"Bergen","year":"2020","journal-title":"Nat. Biotechnol."},{"key":"10.1016\/j.cell.2026.08.032_bib108","doi-asserted-by":"crossref","first-page":"690","DOI":"10.1016\/j.cell.2021.12.045","article-title":"Mapping transcriptomic vector fields of single cells","volume":"185","author":"Qiu","year":"2022","journal-title":"Cell"},{"key":"10.1016\/j.cell.2026.08.032_bib109","doi-asserted-by":"crossref","first-page":"928","DOI":"10.1016\/j.cell.2019.01.006","article-title":"Optimal-Transport Analysis of Single-Cell Gene Expression Identifies Developmental Trajectories in Reprogramming","volume":"176","author":"Schiebinger","year":"2019","journal-title":"Cell"},{"key":"10.1016\/j.cell.2026.08.032_bib110","doi-asserted-by":"crossref","first-page":"1065","DOI":"10.1038\/s41586-024-08453-2","article-title":"Mapping cells through time and space with moscot","volume":"638","author":"Klein","year":"2025","journal-title":"Nature"},{"key":"10.1016\/j.cell.2026.08.032_bib111","doi-asserted-by":"crossref","first-page":"404","DOI":"10.1038\/s41586-021-04237-0","article-title":"Single-cell delineation of lineage and genetic identity in the mouse brain","volume":"601","author":"Bandler","year":"2022","journal-title":"Nature"},{"key":"10.1016\/j.cell.2026.08.032_bib112","doi-asserted-by":"crossref","first-page":"74","DOI":"10.1038\/s41587-021-01006-2","article-title":"Integration of spatial and single-cell transcriptomic data elucidates mouse organogenesis","volume":"40","author":"Lohoff","year":"2022","journal-title":"Nat. Biotechnol."},{"key":"10.1016\/j.cell.2026.08.032_bib113","doi-asserted-by":"crossref","first-page":"111","DOI":"10.1126\/science.abb9536","article-title":"Embryo-scale, single-cell spatial transcriptomics","volume":"373","author":"Srivatsan","year":"2021","journal-title":"Science"},{"key":"10.1016\/j.cell.2026.08.032_bib114","doi-asserted-by":"crossref","first-page":"1176","DOI":"10.1038\/s41588-023-01435-6","article-title":"Spatiotemporal transcriptomic maps of whole mouse embryos at the onset of organogenesis","volume":"55","author":"Sampath Kumar","year":"2023","journal-title":"Nat. Genet."},{"key":"10.1016\/j.cell.2026.08.032_bib115","doi-asserted-by":"crossref","first-page":"1777","DOI":"10.1016\/j.cell.2022.04.003","article-title":"Spatiotemporal transcriptomic atlas of mouse organogenesis using DNA nanoball-patterned arrays","volume":"185","author":"Chen","year":"2022","journal-title":"Cell"},{"key":"10.1016\/j.cell.2026.08.032_bib116","doi-asserted-by":"crossref","DOI":"10.1126\/science.adt3439","article-title":"Whole-embryo spatial transcriptomics at subcellular resolution from gastrulation to organogenesis","volume":"391","author":"Wan","year":"2026","journal-title":"Science"},{"key":"10.1016\/j.cell.2026.08.032_bib117","doi-asserted-by":"crossref","first-page":"442","DOI":"10.1038\/nbt.4103","article-title":"Simultaneous single-cell profiling of lineages and cell types in the vertebrate brain","volume":"36","author":"Raj","year":"2018","journal-title":"Nat. Biotechnol."},{"key":"10.1016\/j.cell.2026.08.032_bib118","doi-asserted-by":"crossref","first-page":"469","DOI":"10.1038\/nbt.4124","article-title":"Simultaneous lineage tracing and cell-type identification using CRISPR\u2013Cas9-induced genetic scars","volume":"36","author":"Spanjaard","year":"2018","journal-title":"Nat. Biotechnol."},{"key":"10.1016\/j.cell.2026.08.032_bib119","doi-asserted-by":"crossref","first-page":"77","DOI":"10.1038\/s41586-019-1184-5","article-title":"Molecular recording of mammalian embryogenesis","volume":"570","author":"Chan","year":"2019","journal-title":"Nature"},{"key":"10.1016\/j.cell.2026.08.032_bib120","doi-asserted-by":"crossref","DOI":"10.1038\/s41467-021-25133-1","article-title":"LineageOT is a unified framework for lineage tracing and trajectory inference","volume":"12","author":"Forrow","year":"2021","journal-title":"Nat. Commun."},{"key":"10.1016\/j.cell.2026.08.032_bib121","doi-asserted-by":"crossref","first-page":"1065","DOI":"10.1126\/science.1162493","article-title":"Reconstruction of Zebrafish Early Embryonic Development by Scanned Light Sheet Microscopy","volume":"322","author":"Keller","year":"2008","journal-title":"Science"},{"key":"10.1016\/j.cell.2026.08.032_bib122","doi-asserted-by":"crossref","first-page":"951","DOI":"10.1038\/nmeth.3036","article-title":"Fast, accurate reconstruction of cell lineages from large-scale fluorescence microscopy data","volume":"11","author":"Amat","year":"2014","journal-title":"Nat. Methods"},{"key":"10.1016\/j.cell.2026.08.032_bib123","doi-asserted-by":"crossref","first-page":"859","DOI":"10.1016\/j.cell.2018.09.031","article-title":"In Toto Imaging and Reconstruction of Post-Implantation Mouse Development at the Single-Cell Level","volume":"175","author":"McDole","year":"2018","journal-title":"Cell"},{"key":"10.1016\/j.cell.2026.08.032_bib124","doi-asserted-by":"crossref","first-page":"410","DOI":"10.1038\/s41576-020-0223-2","article-title":"Lineage tracing meets single-cell omics: opportunities and challenges","volume":"21","author":"Wagner","year":"2020","journal-title":"Nat. Rev. Genet."},{"key":"10.1016\/j.cell.2026.08.032_bib125","doi-asserted-by":"crossref","first-page":"e281","DOI":"10.1016\/S2589-7500(24)00025-6","article-title":"Foresight\u2014a generative pretrained transformer for modelling of patient timelines using electronic health records: a retrospective modelling study","volume":"6","author":"Kraljevic","year":"2024","journal-title":"Lancet Digit. Health"},{"key":"10.1016\/j.cell.2026.08.032_bib126","doi-asserted-by":"crossref","DOI":"10.1038\/s41746-024-01235-0","article-title":"Zero shot health trajectory prediction using transformer","volume":"7","author":"Renc","year":"2024","journal-title":"npj Digit. Med."},{"key":"10.1016\/j.cell.2026.08.032_bib127","article-title":"Generative Medical Event Models Improve with Scale","author":"Waxler","year":"2025","journal-title":"arXiv"},{"key":"10.1016\/j.cell.2026.08.032_bib128","article-title":"A Multimodal and Temporal Foundation Model for Virtual Patient Representations at Healthcare System Scale","author":"Zhang","year":"2026","journal-title":"arXiv"},{"key":"10.1016\/j.cell.2026.08.032_bib129","series-title":"Proceedings of the 39th International Conference on Machine Learning (PMLR)","first-page":"15293","article-title":"Causal Transformer for Estimating Counterfactual Outcomes","author":"Melnychuk","year":"2022"},{"key":"10.1016\/j.cell.2026.08.032_bib130","unstructured":"Li, M.M., Li, K., Ektefaie, Y., Jin, Y., Huang, Y., Messica, S., Cai, T., and Zitnik, M. (2026). Controllable Sequence Editing for Biological and Clinical Trajectories. International Conference on Learning Representations, pp. 14248\u201314290."},{"key":"10.1016\/j.cell.2026.08.032_bib131","doi-asserted-by":"crossref","first-page":"117","DOI":"10.1136\/amiajnl-2012-001145","article-title":"Next-generation phenotyping of electronic health records","volume":"20","author":"Hripcsak","year":"2013","journal-title":"J. Am. Med. Inform. Assoc."},{"key":"10.1016\/j.cell.2026.08.032_bib132","article-title":"Biases in electronic health record data due to processes within the healthcare system: retrospective observational study","volume":"361","author":"Agniel","year":"2018","journal-title":"BMJ"},{"key":"10.1016\/j.cell.2026.08.032_bib133","doi-asserted-by":"crossref","first-page":"1544","DOI":"10.1001\/jamainternmed.2018.3763","article-title":"Potential Biases in Machine Learning Algorithms Using Electronic Health Record Data","volume":"178","author":"Gianfrancesco","year":"2018","journal-title":"JAMA Intern. Med."},{"key":"10.1016\/j.cell.2026.08.032_bib134","doi-asserted-by":"crossref","DOI":"10.1186\/s12874-017-0361-1","article-title":"Limitations of pulmonary embolism ICD-10 codes in emergency department administrative data: let the buyer beware","volume":"17","author":"Burles","year":"2017","journal-title":"BMC Med. Res. Methodol."},{"key":"10.1016\/j.cell.2026.08.032_bib135","doi-asserted-by":"crossref","first-page":"1120","DOI":"10.1002\/acr.20184","article-title":"Electronic medical records for discovery research in rheumatoid arthritis","volume":"62","author":"Liao","year":"2010","journal-title":"Arthritis Care Res."},{"key":"10.1016\/j.cell.2026.08.032_bib136","doi-asserted-by":"crossref","first-page":"733","DOI":"10.1038\/s41586-022-05046-9","article-title":"Live-seq enables temporal transcriptomic recording of single cells","volume":"608","author":"Chen","year":"2022","journal-title":"Nature"},{"key":"10.1016\/j.cell.2026.08.032_bib137","doi-asserted-by":"crossref","first-page":"80","DOI":"10.1038\/s41565-018-0315-8","article-title":"Nanoscale tweezers for single-cell biopsies","volume":"14","author":"Nadappuram","year":"2019","journal-title":"Nat. Nanotechnol."},{"key":"10.1016\/j.cell.2026.08.032_bib138","doi-asserted-by":"crossref","DOI":"10.1126\/sciadv.adl0515","article-title":"Single-cell nanobiopsy enables multigenerational longitudinal transcriptomics of cancer cells","volume":"10","author":"Marcuccio","year":"2024","journal-title":"Sci. Adv."},{"key":"10.1016\/j.cell.2026.08.032_bib139","doi-asserted-by":"crossref","first-page":"3642","DOI":"10.1016\/j.cell.2023.06.013","article-title":"Engineering RNA export for measurement and manipulation of living cells","volume":"186","author":"Horns","year":"2023","journal-title":"Cell"},{"key":"10.1016\/j.cell.2026.08.032_bib140","doi-asserted-by":"crossref","DOI":"10.1038\/s41467-026-72072-w","article-title":"Non-destructive transcriptomics via vesicular export","volume":"17","author":"Armbrust","year":"2026","journal-title":"Nat. Commun."},{"key":"10.1016\/j.cell.2026.08.032_bib141","doi-asserted-by":"crossref","first-page":"1726","DOI":"10.1038\/s41587-023-02082-2","article-title":"Prediction of single-cell RNA expression profiles in live cells by Raman microscopy with Raman2RNA","volume":"42","author":"Kobayashi-Kirschvink","year":"2024","journal-title":"Nat. Biotechnol."},{"key":"10.1016\/j.cell.2026.08.032_bib142","doi-asserted-by":"crossref","DOI":"10.1126\/science.adz9353","article-title":"A genetically encoded device for transcriptome storage in mammalian cells","volume":"391","author":"Chao","year":"2026","journal-title":"Science"},{"key":"10.1016\/j.cell.2026.08.032_bib143","doi-asserted-by":"crossref","first-page":"1073","DOI":"10.1038\/s41586-024-07706-4","article-title":"Symbolic recording of signalling and cis-regulatory element activity to DNA","volume":"632","author":"Chen","year":"2024","journal-title":"Nature"},{"key":"10.1016\/j.cell.2026.08.032_bib144","doi-asserted-by":"crossref","first-page":"1010","DOI":"10.1038\/s41586-025-09151-3","article-title":"Morphodynamics of human early brain organoid development","volume":"644","author":"Jain","year":"2025","journal-title":"Nature"},{"key":"10.1016\/j.cell.2026.08.032_bib145","doi-asserted-by":"crossref","first-page":"1836","DOI":"10.1038\/s41587-023-02081-3","article-title":"Kirigami electronics for long-term electrophysiological recording of human neural organoids and assembloids","volume":"42","author":"Yang","year":"2024","journal-title":"Nat. Biotechnol."},{"key":"10.1016\/j.cell.2026.08.032_bib146","doi-asserted-by":"crossref","first-page":"373","DOI":"10.1038\/s41586-023-06473-y","article-title":"Single-cell brain organoid screening identifies developmental defects in autism","volume":"621","author":"Li","year":"2023","journal-title":"Nature"},{"key":"10.1016\/j.cell.2026.08.032_bib147","doi-asserted-by":"crossref","first-page":"359","DOI":"10.1038\/s41586-023-06564-w","article-title":"Assembloid CRISPR screens reveal impact of disease genes in human neurodevelopment","volume":"622","author":"Meng","year":"2023","journal-title":"Nature"},{"key":"10.1016\/j.cell.2026.08.032_bib148","doi-asserted-by":"crossref","first-page":"465","DOI":"10.1038\/s41592-025-02927-5","article-title":"Systematic scRNA-seq screens profile neural organoid response to morphogens","volume":"23","author":"Sanch\u00eds-Calleja","year":"2026","journal-title":"Nat. Methods"},{"key":"10.1016\/j.cell.2026.08.032_bib149","doi-asserted-by":"crossref","DOI":"10.1126\/sciadv.adt1851","article-title":"Machine learning-assisted exploration of multidrug-drug administration regimens for organoid arrays","volume":"11","author":"Yakavets","year":"2025","journal-title":"Sci. Adv."},{"key":"10.1016\/j.cell.2026.08.032_bib150","doi-asserted-by":"crossref","DOI":"10.1038\/s41467-025-62818-3","article-title":"Large-scale CRISPR screening in primary human 3D gastric organoids enables comprehensive dissection of gene-drug interactions","volume":"16","author":"Lo","year":"2025","journal-title":"Nat. Commun."},{"key":"10.1016\/j.cell.2026.08.032_bib151","doi-asserted-by":"crossref","first-page":"142","DOI":"10.1038\/s41586-024-07578-8","article-title":"Brain Chimeroids reveal individual susceptibility to neurotoxic triggers","volume":"631","author":"Ant\u00f3n-Bola\u00f1os","year":"2024","journal-title":"Nature"},{"key":"10.1016\/j.cell.2026.08.032_bib152","doi-asserted-by":"crossref","first-page":"421","DOI":"10.1038\/s41551-019-0498-9","article-title":"Quantitative prediction of human pharmacokinetic responses to drugs via fluidically coupled vascularized organ chips","volume":"4","author":"Herland","year":"2020","journal-title":"Nat. Biomed. Eng."},{"key":"10.1016\/j.cell.2026.08.032_bib153","doi-asserted-by":"crossref","first-page":"407","DOI":"10.1038\/s41551-019-0497-x","article-title":"Robotic fluidic coupling and interrogation of multiple vascularized organ chips","volume":"4","author":"Novak","year":"2020","journal-title":"Nat. Biomed. Eng."},{"key":"10.1016\/j.cell.2026.08.032_bib154","first-page":"1","article-title":"Digital twins of ex vivo human lungs enable accurate and personalized evaluation of therapeutic efficacy","author":"Zhou","year":"2026","journal-title":"Nat. Biotechnol."},{"key":"10.1016\/j.cell.2026.08.032_bib155","doi-asserted-by":"crossref","first-page":"218","DOI":"10.1038\/s41586-025-09847-6","article-title":"Physiology and immunology of a pig-to-human decedent kidney xenotransplant","volume":"650","author":"Montgomery","year":"2026","journal-title":"Nature"},{"key":"10.1016\/j.cell.2026.08.032_bib156","doi-asserted-by":"crossref","first-page":"205","DOI":"10.1038\/s41586-025-09846-7","article-title":"Multi-omics analysis of a pig-to-human decedent kidney xenotransplant","volume":"650","author":"Schmauch","year":"2026","journal-title":"Nature"},{"key":"10.1016\/j.cell.2026.08.032_bib157","doi-asserted-by":"crossref","first-page":"612","DOI":"10.1038\/d41586-022-01618-x","article-title":"Cloud labs: where robots do the research","volume":"606","author":"Arnold","year":"2022","journal-title":"Nature"},{"key":"10.1016\/j.cell.2026.08.032_bib158","doi-asserted-by":"crossref","DOI":"10.1371\/journal.pbio.3001919","article-title":"Support academic access to automated cloud labs to improve reproducibility","volume":"21","author":"Armer","year":"2023","journal-title":"PLOS Biol."},{"key":"10.1016\/j.cell.2026.08.032_bib159","article-title":"Building a biofoundry","volume":"6","author":"Holowko","year":"2021","journal-title":"Synth. Biol. (Oxf)"},{"key":"10.1016\/j.cell.2026.08.032_bib160","doi-asserted-by":"crossref","DOI":"10.1038\/s41467-025-59231-1","article-title":"Science acceleration and accessibility with self-driving labs","volume":"16","author":"Canty","year":"2025","journal-title":"Nat. Commun."},{"key":"10.1016\/j.cell.2026.08.032_bib161","doi-asserted-by":"crossref","unstructured":"Fu, K., Lyu, L., Li, S., Huang, S., Xu, S., Zheng, J., Liu, X., Liu, S., Barbone, G., Liu, Y., et al. (2026). Agentic Laboratories of the Future: Towards World Models for Scientific Discovery. https:\/\/doi.org\/10.20944\/preprints202608.0213.v1.","DOI":"10.20944\/preprints202608.0213.v1"},{"key":"10.1016\/j.cell.2026.08.032_bib162","article-title":"Towards Human-Led, Agent-Driven Autonomous Laboratories for the Life Sciences","author":"Cheng","year":"2026","journal-title":"Preprints"},{"key":"10.1016\/j.cell.2026.08.032_bib163","doi-asserted-by":"crossref","first-page":"389","DOI":"10.1038\/s41592-021-01100-y","article-title":"Low-N protein engineering with data-efficient deep learning","volume":"18","author":"Biswas","year":"2021","journal-title":"Nat. Methods"},{"key":"10.1016\/j.cell.2026.08.032_bib164","doi-asserted-by":"crossref","first-page":"633","DOI":"10.1016\/j.cels.2023.04.006","article-title":"In vitro continuous protein evolution empowered by machine learning and automation","volume":"14","author":"Yu","year":"2023","journal-title":"Cell Syst."},{"key":"10.1016\/j.cell.2026.08.032_bib165","article-title":"Integrating protein language models and automatic biofoundry for enhanced protein evolution","volume":"16","author":"Zhang","year":"2025","journal-title":"Nat. Commun."},{"key":"10.1016\/j.cell.2026.08.032_bib166","doi-asserted-by":"crossref","first-page":"1620","DOI":"10.1016\/j.cell.2026.01.012","article-title":"LUMI-lab: A foundation model-driven autonomous platform enabling discovery of ionizable lipid designs for mRNA delivery","volume":"189","author":"Xu","year":"2026","journal-title":"Cell"},{"key":"10.1016\/j.cell.2026.08.032_bib167","doi-asserted-by":"crossref","DOI":"10.1038\/s41467-024-55287-7","article-title":"A Bayesian active learning platform for scalable combination drug screens","volume":"16","author":"Tosh","year":"2025","journal-title":"Nat Commun"},{"key":"10.1016\/j.cell.2026.08.032_bib168","doi-asserted-by":"crossref","first-page":"18142","DOI":"10.1073\/pnas.1900548116","article-title":"Closed-loop cycles of experiment design, execution, and learning accelerate systems biology model development in yeast","volume":"116","author":"Coutant","year":"2019","journal-title":"Proc. Natl. Acad. Sci. USA"},{"key":"10.1016\/j.cell.2026.08.032_bib169","doi-asserted-by":"crossref","first-page":"1360","DOI":"10.1038\/s44320-026-00221-w","article-title":"Active learning-guided mechanistic modeling reveals context-specific regulators of CXCL9 expression in pancreatic cancer cells","volume":"22","author":"Wang","year":"2026","journal-title":"Mol. Syst. Biol."},{"key":"10.1016\/j.cell.2026.08.032_bib170","doi-asserted-by":"crossref","first-page":"w107","DOI":"10.1377\/hlthaff.26.2.w107","article-title":"A Rapid-Learning Health System?","volume":"26","author":"Etheredge","year":"2007","journal-title":"Health Aff. (Millwood)"},{"key":"10.1016\/j.cell.2026.08.032_bib171","doi-asserted-by":"crossref","DOI":"10.1126\/scitranslmed.3001456","article-title":"Achieving a Nationwide Learning Health System","volume":"2","author":"Friedman","year":"2010","journal-title":"Sci. Transl. Med."},{"key":"10.1016\/j.cell.2026.08.032_bib172","doi-asserted-by":"crossref","first-page":"329","DOI":"10.1038\/s41586-023-06592-6","article-title":"Plasma proteomic associations with genetics and health in the UK Biobank","volume":"622","author":"Sun","year":"2023","journal-title":"Nature"},{"key":"10.1016\/j.cell.2026.08.032_bib173","doi-asserted-by":"crossref","first-page":"191","DOI":"10.1038\/s41576-024-00794-y","article-title":"Biobanking with genetics shapes precision medicine and global health","volume":"26","author":"Gallagher","year":"2025","journal-title":"Nat. Rev. Genet."},{"key":"10.1016\/j.cell.2026.08.032_bib174","doi-asserted-by":"crossref","first-page":"454","DOI":"10.1056\/NEJMra1510059","article-title":"Pragmatic Trials","volume":"375","author":"Ford","year":"2016","journal-title":"N. Engl. J. Med."},{"key":"10.1016\/j.cell.2026.08.032_bib175","doi-asserted-by":"crossref","first-page":"312","DOI":"10.1038\/nrcardio.2015.33","article-title":"Registry-based randomized clinical trials\u2014a new clinical trial paradigm","volume":"12","author":"James","year":"2015","journal-title":"Nat. Rev. Cardiol."},{"key":"10.1016\/j.cell.2026.08.032_bib176","doi-asserted-by":"crossref","first-page":"797","DOI":"10.1038\/s41573-019-0034-3","article-title":"Adaptive platform trials: definition, design, conduct and reporting considerations","volume":"18","author":"Angus","year":"2019","journal-title":"Nat. Rev. Drug Discov."},{"key":"10.1016\/j.cell.2026.08.032_bib177","doi-asserted-by":"crossref","first-page":"336","DOI":"10.1001\/jama.2022.24324","article-title":"Sequential, Multiple Assignment, Randomized Trial Designs","volume":"329","author":"Kidwell","year":"2023","journal-title":"JAMA"},{"key":"10.1016\/j.cell.2026.08.032_bib178","doi-asserted-by":"crossref","first-page":"758","DOI":"10.1093\/aje\/kwv254","article-title":"Using Big Data to Emulate a Target Trial When a Randomized Trial Is Not Available","volume":"183","author":"Hern\u00e1n","year":"2016","journal-title":"Am. J. Epidemiol."},{"key":"10.1016\/j.cell.2026.08.032_bib179","doi-asserted-by":"crossref","first-page":"2446","DOI":"10.1001\/jama.2022.21383","article-title":"Target Trial Emulation: A Framework for Causal Inference From Observational Data","volume":"328","author":"Hern\u00e1n","year":"2022","journal-title":"JAMA"},{"key":"10.1016\/j.cell.2026.08.032_bib180","doi-asserted-by":"crossref","DOI":"10.1038\/s41467-023-43929-1","article-title":"High-throughput target trial emulation for Alzheimer\u2019s disease drug repurposing with real-world data","volume":"14","author":"Zang","year":"2023","journal-title":"Nat. Commun."},{"key":"10.1016\/j.cell.2026.08.032_bib181","doi-asserted-by":"crossref","first-page":"1376","DOI":"10.1001\/jama.2023.4221","article-title":"Emulation of randomized clinical trials With nonrandomized database analyses: Results of 32 clinical trials","volume":"329","author":"Wang","year":"2023","journal-title":"JAMA"},{"key":"10.1016\/j.cell.2026.08.032_bib182","doi-asserted-by":"crossref","DOI":"10.1038\/s41467-026-74999-6","article-title":"Evaluating bias in target trial emulation for heart failure across statistical and deep learning methods","volume":"17","author":"Fan","year":"2026","journal-title":"Nat. Commun."},{"key":"10.1016\/j.cell.2026.08.032_bib183","doi-asserted-by":"crossref","DOI":"10.1056\/AIoa2400859","article-title":"TRIALSCOPE \u2014 A Framework for Clinical Trial Simulation from Real-World Data","volume":"2","author":"Gonz\u00e1lez","year":"2025","journal-title":"NEJM AI"},{"key":"10.1016\/j.cell.2026.08.032_bib184","article-title":"Can generative artificial intelligence empower target trial emulations?","volume":"8","author":"Guan","year":"2026","journal-title":"Lancet Digit. Health"},{"key":"10.1016\/j.cell.2026.08.032_bib185","article-title":"Empowering clinical trial design with agentic intelligence and real-world data","volume":"17","author":"Li","year":"2026","journal-title":"Nat. Commun."},{"key":"10.1016\/j.cell.2026.08.032_bib186","article-title":"Agentic Trial Emulation to Learn Health System-specific Drug Effects At Scale","author":"Kauffman","year":"2026","journal-title":"medRxiv"},{"key":"10.1016\/j.cell.2026.08.032_bib187","doi-asserted-by":"crossref","first-page":"991","DOI":"10.1038\/s44222-024-00245-7","article-title":"Synthetic data in biomedicine via generative artificial intelligence","volume":"2","author":"van Breugel","year":"2024","journal-title":"Nat Rev. Bioeng."},{"key":"10.1016\/j.cell.2026.08.032_bib188","doi-asserted-by":"crossref","DOI":"10.1371\/journal.pcbi.1005991","article-title":"PhysiCell: An open source physics-based cell simulator for 3-D multicellular systems","volume":"14","author":"Ghaffarizadeh","year":"2018","journal-title":"PLOS Comput. Biol."},{"key":"10.1016\/j.cell.2026.08.032_bib189","doi-asserted-by":"crossref","first-page":"247","DOI":"10.1038\/s41587-023-01772-1","article-title":"scDesign3 generates realistic in silico data for multimodal single-cell and spatial omics","volume":"42","author":"Song","year":"2024","journal-title":"Nat. Biotechnol."},{"key":"10.1016\/j.cell.2026.08.032_bib190","doi-asserted-by":"crossref","DOI":"10.1038\/s41746-023-00834-7","article-title":"Generating synthetic mixed-type longitudinal electronic health records for artificial intelligent applications","volume":"6","author":"Li","year":"2023","journal-title":"npj Digit. Med."},{"key":"10.1016\/j.cell.2026.08.032_bib191","doi-asserted-by":"crossref","first-page":"8327","DOI":"10.1039\/D6SC01189F","article-title":"Black-box data: a new paradigm for biomedicine in the AI era","volume":"17","author":"Naef","year":"2026","journal-title":"Chem. Sci."},{"key":"10.1016\/j.cell.2026.08.032_bib192","doi-asserted-by":"crossref","DOI":"10.1038\/sdata.2016.18","article-title":"The FAIR Guiding Principles for scientific data management and stewardship","volume":"3","author":"Wilkinson","year":"2016","journal-title":"Sci. Data"},{"key":"10.1016\/j.cell.2026.08.032_bib193","doi-asserted-by":"crossref","first-page":"121","DOI":"10.1038\/ng.1054","article-title":"Toward interoperable bioscience data","volume":"44","author":"Sansone","year":"2012","journal-title":"Nat. Genet."},{"key":"10.1016\/j.cell.2026.08.032_bib194","doi-asserted-by":"crossref","DOI":"10.1056\/AIra2501253","article-title":"MEDS \u2014 An Emerging Data Standard and Ecosystem for Health AI Research","volume":"3","author":"McDermott","year":"2026","journal-title":"NEJM AI"},{"key":"10.1016\/j.cell.2026.08.032_bib195","article-title":"A Global Log for Medical AI","author":"Noori","year":"2026","journal-title":"arXiv"},{"key":"10.1016\/j.cell.2026.08.032_bib196","doi-asserted-by":"crossref","DOI":"10.1038\/s41746-020-00323-1","article-title":"The future of digital health with federated learning","volume":"3","author":"Rieke","year":"2020","journal-title":"npj Digit. Med."},{"key":"10.1016\/j.cell.2026.08.032_bib197","article-title":"Chreode: a Cell World Model for One-Step Temporal Dynamics and Perturbation Prediction","author":"Qiu","year":"2026","journal-title":"arXiv"},{"key":"10.1016\/j.cell.2026.08.032_bib198","unstructured":"Radford, A., Kim, J.W., Hallacy, C., Ramesh, A., Goh, G., Agarwal, S., Sastry, G., Askell, A., Mishkin, P., Clark, J., et al. (2021). Learning Transferable Visual Models From Natural Language Supervision. In Proceedings of the 38th International Conference on Machine Learning (PMLR), pp. 8748\u20138763."},{"key":"10.1016\/j.cell.2026.08.032_bib199","doi-asserted-by":"crossref","first-page":"696","DOI":"10.1038\/s42256-022-00518-z","article-title":"Contrastive learning enables rapid mapping to multimodal single-cell atlas of multimillion scale","volume":"4","author":"Yang","year":"2022","journal-title":"Nat. Mach. Intell."},{"key":"10.1016\/j.cell.2026.08.032_bib200","doi-asserted-by":"crossref","DOI":"10.1038\/s41467-026-72882-y","article-title":"CAPTAIN: a multimodal foundation model pretrained on co-assayed single-cell RNA and protein","volume":"17","author":"Ji","year":"2026","journal-title":"Nat. Commun."},{"key":"10.1016\/j.cell.2026.08.032_bib201","article-title":"BABEL enables cross-modality translation between multiomic profiles at single-cell resolution","volume":"118","author":"Wu","year":"2021","journal-title":"Proc. Natl. Acad. Sci. USA"},{"key":"10.1016\/j.cell.2026.08.032_bib202","article-title":"scButterfly: a versatile single-cell cross-modality translation method via dual-aligned variational autoencoders","volume":"15","author":"Cao","year":"2024","journal-title":"Nat. Commun."},{"key":"10.1016\/j.cell.2026.08.032_bib203","doi-asserted-by":"crossref","first-page":"1222","DOI":"10.1038\/s41592-023-01909-9","article-title":"MultiVI: deep generative model for the integration of multimodal data","volume":"20","author":"Ashuach","year":"2023","journal-title":"Nat. Methods"},{"key":"10.1016\/j.cell.2026.08.032_bib204","doi-asserted-by":"crossref","first-page":"1594","DOI":"10.1038\/s41587-023-02040-y","article-title":"Mosaic integration and knowledge transfer of single-cell multimodal data with MIDAS","volume":"42","author":"He","year":"2024","journal-title":"Nat. Biotechnol."},{"key":"10.1016\/j.cell.2026.08.032_bib205","doi-asserted-by":"crossref","first-page":"1352","DOI":"10.1038\/s41592-021-01264-7","article-title":"Deep learning and alignment of spatially resolved single-cell transcriptomes with Tangram","volume":"18","author":"Biancalani","year":"2021","journal-title":"Nat. Methods"},{"key":"10.1016\/j.cell.2026.08.032_bib206","doi-asserted-by":"crossref","first-page":"1458","DOI":"10.1038\/s41587-022-01284-4","article-title":"Multi-omics single-cell data integration and regulatory inference with graph-linked embedding","volume":"40","author":"Cao","year":"2022","journal-title":"Nat. Biotechnol."},{"key":"10.1016\/j.cell.2026.08.032_bib207","doi-asserted-by":"crossref","first-page":"1096","DOI":"10.1038\/s41587-023-01935-0","article-title":"Integration of spatial and single-cell data across modalities with weakly linked features","volume":"42","author":"Chen","year":"2024","journal-title":"Nat. Biotechnol."},{"key":"10.1016\/j.cell.2026.08.032_bib208","doi-asserted-by":"crossref","first-page":"293","DOI":"10.1038\/s41587-023-01767-y","article-title":"Dictionary learning for integrative, multimodal and scalable single-cell analysis","volume":"42","author":"Hao","year":"2024","journal-title":"Nat. Biotechnol."},{"key":"10.1016\/j.cell.2026.08.032_bib209","first-page":"27299","article-title":"2Sentence: Teaching Large Language Models the Language of Biology. In Proceedings of the 41st International Conference on Machine Learning (PMLR)","author":"Levine","year":"2024","journal-title":"Cell"},{"key":"10.1016\/j.cell.2026.08.032_bib210","article-title":"ProCyon: A multimodal foundation model for protein phenotypes","author":"Queen","year":"2025","journal-title":"bioRxiv"},{"key":"10.1016\/j.cell.2026.08.032_bib211","series-title":"Adv. Neural Inf. Process. Syst.","first-page":"111644","article-title":"BioReason: Incentivizing Multimodal Biological Reasoning within a DNA-LLM Model","author":"Fallahpour","year":"2025"},{"key":"10.1016\/j.cell.2026.08.032_bib212","article-title":"BioReason-Pro: Advancing Protein Function Prediction with Multimodal Biological Reasoning","author":"Fallahpour","year":"2026","journal-title":"bioRxiv"},{"key":"10.1016\/j.cell.2026.08.032_bib213","first-page":"1","article-title":"Multimodal learning enables chat-based exploration of single-cell data","author":"Schaefer","year":"2025","journal-title":"Nat. Biotechnol."},{"key":"10.1016\/j.cell.2026.08.032_bib214","first-page":"24804","article-title":"CSDI: Conditional Score-based Diffusion Models for Probabilistic Time Series Imputation","volume":"34","author":"Tashiro","year":"2021","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"10.1016\/j.cell.2026.08.032_bib215","doi-asserted-by":"crossref","first-page":"16083","DOI":"10.52202\/075280-0707","article-title":"Any-to-Any Generation via Composable Diffusion","volume":"36","author":"Tang","year":"2023","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"10.1016\/j.cell.2026.08.032_bib216","unstructured":"Bao, F., Nie, S., Xue, K., Li, C., Pu, S., Wang, Y., Yue, G., Cao, Y., Su, H., and Zhu, J. (2023). One Transformer Fits All Distributions in Multi-Modal Diffusion at Scale. In Proceedings of the 40th International Conference on Machine Learning (PMLR), pp. 1692\u20131717."},{"key":"10.1016\/j.cell.2026.08.032_bib217","doi-asserted-by":"crossref","unstructured":"Li, S., Kallidromitis, K., Gokul, A., Liao, Z., Kato, Y., Kozuka, K., and Grover, A. (2025). OmniFlow: Any-to-Any Generation with Multi-Modal Rectified Flows. In pp. 13178\u201313188.","DOI":"10.1109\/CVPR52734.2025.01230"},{"key":"10.1016\/j.cell.2026.08.032_bib218","doi-asserted-by":"crossref","unstructured":"Assran, M., Duval, Q., Misra, I., Bojanowski, P., Vincent, P., Rabbat, M., LeCun, Y., and Ballas, N. (2023). Self-Supervised Learning From Images With a Joint-Embedding Predictive Architecture. In pp. 15619\u201315629.","DOI":"10.1109\/CVPR52729.2023.01499"},{"key":"10.1016\/j.cell.2026.08.032_bib219","article-title":"Revisiting Feature Prediction for Learning Visual Representations from Video","author":"Bardes","year":"2024","journal-title":"arXiv"},{"key":"10.1016\/j.cell.2026.08.032_bib220","unstructured":"Hafner, D., Lillicrap, T., Fischer, I., Villegas, R., Ha, D., Lee, H., and Davidson, J. (2019). Learning Latent Dynamics for Planning from Pixels. In Proceedings of the 36th International Conference on Machine Learning (PMLR), pp. 2555\u20132565."},{"key":"10.1016\/j.cell.2026.08.032_bib221","doi-asserted-by":"crossref","DOI":"10.15252\/msb.202211517","article-title":"Predicting cellular responses to complex perturbations in high-throughput screens","volume":"19","author":"Lotfollahi","year":"2023","journal-title":"Mol. Syst. Biol."},{"key":"10.1016\/j.cell.2026.08.032_bib222","doi-asserted-by":"crossref","first-page":"786","DOI":"10.1126\/science.aax4438","article-title":"Exploring genetic interaction manifolds constructed from rich single-cell phenotypes","volume":"365","author":"Norman","year":"2019","journal-title":"Science"},{"key":"10.1016\/j.cell.2026.08.032_bib223","series-title":"Adv. Neural Inf. Process. Syst.","article-title":"Deep Sets","author":"Zaheer","year":"2017"},{"key":"10.1016\/j.cell.2026.08.032_bib224","unstructured":"Lee, J., Lee, Y., Kim, J., Kosiorek, A., Choi, S., and Teh, Y.W. (2019). Set Transformer: A Framework for Attention-based Permutation-Invariant Neural Networks. In Proceedings of the 36th International Conference on Machine Learning (PMLR), pp. 3744\u20133753."},{"key":"10.1016\/j.cell.2026.08.032_bib225","doi-asserted-by":"crossref","first-page":"511","DOI":"10.1038\/s41586-019-1103-9","article-title":"Prioritization of cancer therapeutic targets using CRISPR\u2013Cas9 screens","volume":"568","author":"Behan","year":"2019","journal-title":"Nature"},{"key":"10.1016\/j.cell.2026.08.032_bib226","article-title":"Unifying Biomedical Knowledge in a Modern Multimodal Graph","author":"Vittor","year":"2026","journal-title":"arXiv"},{"key":"10.1016\/j.cell.2026.08.032_bib227","series-title":"Adv. Neural Inf. Process. Syst.","article-title":"Removing Hidden Confounding by Experimental Grounding","author":"Kallus","year":"2018"},{"key":"10.1016\/j.cell.2026.08.032_bib228","doi-asserted-by":"crossref","first-page":"1759","DOI":"10.1038\/s41592-023-01969-x","article-title":"Learning single-cell perturbation responses using neural optimal transport","volume":"20","author":"Bunne","year":"2023","journal-title":"Nat. Methods"},{"key":"10.1016\/j.cell.2026.08.032_bib229","article-title":"Generative Distribution Embeddings: Lifting autoencoders to the space of distributions for multiscale representation learning","volume":"38","author":"Fishman","year":"2026","journal-title":"ArXiv"},{"key":"10.1016\/j.cell.2026.08.032_bib230","series-title":"Adv. Neural Inf. Process. Syst.","first-page":"1273","article-title":"Offline Reinforcement Learning as One Big Sequence Modeling Problem","author":"Janner","year":"2021"},{"key":"10.1016\/j.cell.2026.08.032_bib231","article-title":"Dream to Control: Learning Behaviors by Latent Imagination","author":"Hafner","year":"2020","journal-title":"arXiv"},{"key":"10.1016\/j.cell.2026.08.032_bib232","article-title":"Mastering Atari with Discrete World Models","author":"Hafner","year":"2022","journal-title":"arXiv"},{"key":"10.1016\/j.cell.2026.08.032_bib233","unstructured":"Janner, M., Du, Y., Tenenbaum, J., and Levine, S. (2022). Planning with Diffusion for Flexible Behavior Synthesis. In Proceedings of the 39th International Conference on Machine Learning (PMLR), pp. 9902\u20139915."},{"key":"10.1016\/j.cell.2026.08.032_bib234","series-title":"Adv. Neural Inf. Process. Syst.","first-page":"58757","article-title":"Diffusion for World Modeling: Visual Details Matter in Atari","author":"Alonso","year":"2024"},{"key":"10.1016\/j.cell.2026.08.032_bib235","doi-asserted-by":"crossref","first-page":"2539","DOI":"10.1038\/s41592-025-02899-6","article-title":"Novae: a graph-based foundation model for spatial transcriptomics data","volume":"22","author":"Blampey","year":"2025","journal-title":"Nat. Methods"},{"key":"10.1016\/j.cell.2026.08.032_bib236","doi-asserted-by":"crossref","first-page":"377","DOI":"10.1038\/s43018-021-00195-8","article-title":"Overcoming therapy resistance in EGFR-mutant lung cancer","volume":"2","author":"Passaro","year":"2021","journal-title":"Nat. Cancer"},{"key":"10.1016\/j.cell.2026.08.032_bib237","series-title":"Adv. Neural Inf. Process. Syst.","article-title":"When to Trust Your Model: Model-Based Policy Optimization","author":"Janner","year":"2019"},{"key":"10.1016\/j.cell.2026.08.032_bib238","article-title":"Self-Correcting Models for Model-Based Reinforcement Learning","volume":"31","author":"Talvitie","year":"2017","journal-title":"Proceedings of the AAAI Conference on Artificial Intelligence 31"},{"key":"10.1016\/j.cell.2026.08.032_bib239","unstructured":"Asadi, K., Misra, D., and Littman, M. (2018). Lipschitz Continuity in Model-based Reinforcement Learning. In Proceedings of the 35th International Conference on Machine Learning (PMLR), pp. 264\u2013273."},{"key":"10.1016\/j.cell.2026.08.032_bib240","article-title":"Investigating Compounding Prediction Errors in Learned Dynamics Models","author":"Lambert","year":"2022","journal-title":"arXiv"},{"key":"10.1016\/j.cell.2026.08.032_bib241","series-title":"Adv. Neural Inf. Process. Syst.","article-title":"Latent Ordinary Differential Equations for Irregularly-Sampled Time Series","author":"Rubanova","year":"2019"},{"key":"10.1016\/j.cell.2026.08.032_bib242","first-page":"6696","article-title":"Neural Controlled Differential Equations for Irregular Time Series","volume":"33","author":"Kidger","year":"2020","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"10.1016\/j.cell.2026.08.032_bib243","doi-asserted-by":"crossref","first-page":"1683","DOI":"10.1038\/s41592-023-02035-2","article-title":"Population-level integration of single-cell datasets enables multi-scale analysis across samples","volume":"20","author":"De Donno","year":"2023","journal-title":"Nat. Methods"},{"key":"10.1016\/j.cell.2026.08.032_bib244","doi-asserted-by":"crossref","first-page":"2264","DOI":"10.1038\/s41592-025-02808-x","article-title":"Deep generative modeling of sample-level heterogeneity in single-cell genomics","volume":"22","author":"Boyeau","year":"2025","journal-title":"Nat. Methods"},{"key":"10.1016\/j.cell.2026.08.032_bib245","doi-asserted-by":"crossref","first-page":"897","DOI":"10.1038\/s41588-025-02120-6","article-title":"Quantitative characterization of cell niches in spatially resolved omics data","volume":"57","author":"Birk","year":"2025","journal-title":"Nat. Genet."},{"key":"10.1016\/j.cell.2026.08.032_bib246","doi-asserted-by":"crossref","DOI":"10.1038\/s41467-022-32465-z","article-title":"Multiscale light-sheet organoid imaging framework","volume":"13","author":"de Medeiros","year":"2022","journal-title":"Nat. Commun."},{"key":"10.1016\/j.cell.2026.08.032_bib247","doi-asserted-by":"crossref","first-page":"2034","DOI":"10.1038\/s41592-023-02080-x","article-title":"In vitro modeling of the human dopaminergic system using spatially arranged ventral midbrain\u2013striatum\u2013cortex assembloids","volume":"20","author":"Reumann","year":"2023","journal-title":"Nat. Methods"},{"key":"10.1016\/j.cell.2026.08.032_bib248","doi-asserted-by":"crossref","first-page":"1421","DOI":"10.1038\/s41587-020-00763-w","article-title":"Generation of human striatal organoids and cortico-striatal assembloids from human pluripotent stem cells","volume":"38","author":"Miura","year":"2020","journal-title":"Nat. Biotechnol."},{"key":"10.1016\/j.cell.2026.08.032_bib249","doi-asserted-by":"crossref","first-page":"1444","DOI":"10.1038\/s41592-024-02362-y","article-title":"Guiding questions to avoid data leakage in biological machine learning applications","volume":"21","author":"Bernett","year":"2024","journal-title":"Nat. Methods"},{"key":"10.1016\/j.cell.2026.08.032_bib250","doi-asserted-by":"crossref","first-page":"1512","DOI":"10.1038\/s42256-024-00931-6","article-title":"Evaluating generalizability of artificial intelligence models for molecular datasets","volume":"6","author":"Ektefaie","year":"2024","journal-title":"Nat. Mach. Intell."},{"key":"10.1016\/j.cell.2026.08.032_bib251","doi-asserted-by":"crossref","DOI":"10.1038\/s41467-025-58606-8","article-title":"Data splitting to avoid information leakage with DataSAIL","volume":"16","author":"Joeres","year":"2025","journal-title":"Nat. Commun."},{"key":"10.1016\/j.cell.2026.08.032_bib252","article-title":"PerturBench: Benchmarking Machine Learning Models for Cellular Perturbation Analysis","author":"Wu","year":"2024","journal-title":"arXiv"},{"key":"10.1016\/j.cell.2026.08.032_bib253","doi-asserted-by":"crossref","DOI":"10.1038\/s41467-021-23518-w","article-title":"Generative modeling of single-cell time series with PRESCIENT enables prediction of cell trajectories with interventions","volume":"12","author":"Yeo","year":"2021","journal-title":"Nat. Commun."},{"key":"10.1016\/j.cell.2026.08.032_bib254","doi-asserted-by":"crossref","DOI":"10.1038\/s41467-024-55707-8","article-title":"Predicting cell morphological responses to perturbations using generative modeling","volume":"16","author":"Palma","year":"2025","journal-title":"Nat. Commun."},{"key":"10.1016\/j.cell.2026.08.032_bib255","doi-asserted-by":"crossref","first-page":"4159","DOI":"10.1016\/j.cell.2026.04.028","article-title":"D-SPIN constructs regulatory network models from scRNA-seq that reveal organizing principles of perturbation response","volume":"189","author":"Jiang","year":"2026","journal-title":"Cell"},{"key":"10.1016\/j.cell.2026.08.032_bib256","doi-asserted-by":"crossref","unstructured":"Wenteler, A., Occhetta, M., Branson, N., Curean, V., Huebner, M., Dee, W., Connell, W., Chung, S.P., Hawkins-Hooker, A., Ektefaie, Y., et al. (2025). PertEval-scFM: Benchmarking Single-Cell Foundation Models for Perturbation Effect Prediction. In Proceedings of the 42nd International Conference on Machine Learning (PMLR), pp. 66633\u201366677.","DOI":"10.1101\/2024.10.02.616248"},{"key":"10.1016\/j.cell.2026.08.032_bib257","doi-asserted-by":"crossref","first-page":"2525","DOI":"10.1038\/s41592-025-02814-z","article-title":"Nicheformer: a foundation model for single-cell and spatial omics","volume":"22","author":"Tejada-Lapuerta","year":"2025","journal-title":"Nat. Methods"},{"key":"10.1016\/j.cell.2026.08.032_bib258","doi-asserted-by":"crossref","DOI":"10.1063\/1.3565032","article-title":"Markov models of molecular kinetics: Generation and validation","volume":"134","author":"Prinz","year":"2011","journal-title":"J. Chem. Phys."},{"key":"10.1016\/j.cell.2026.08.032_bib259","doi-asserted-by":"crossref","first-page":"1699","DOI":"10.1093\/bib\/bby043","article-title":"In silico clinical trials: concepts and early adoptions","volume":"20","author":"Pappalardo","year":"2019","journal-title":"Brief. Bioinform."},{"key":"10.1016\/j.cell.2026.08.032_bib260","article-title":"Using AI-generated digital twins to boost clinical trial efficiency in Alzheimer\u2019s disease","volume":"11","author":"Wang","year":"2025","journal-title":"Alzheimers. Dement. (N Y)"},{"key":"10.1016\/j.cell.2026.08.032_bib261","doi-asserted-by":"crossref","first-page":"1658","DOI":"10.1609\/aaai.v33i01.33011658","article-title":"Melding the Data-Decisions Pipeline: Decision-Focused Learning for Combinatorial Optimization","volume":"33","author":"Wilder","year":"2019","journal-title":"Proceedings of the AAAI Conference on Artificial Intelligence 33"},{"key":"10.1016\/j.cell.2026.08.032_bib262","doi-asserted-by":"crossref","first-page":"792","DOI":"10.1038\/s41586-023-06725-x","article-title":"CD201+ fascia progenitors choreograph injury repair","volume":"623","author":"Correa-Gallegos","year":"2023","journal-title":"Nature"},{"key":"10.1016\/j.cell.2026.08.032_bib263","doi-asserted-by":"crossref","first-page":"1227","DOI":"10.1038\/s41588-022-01129-5","article-title":"Origin and function of activated fibroblast states during zebrafish heart regeneration","volume":"54","author":"Hu","year":"2022","journal-title":"Nat. Genet."},{"key":"10.1016\/j.cell.2026.08.032_bib264","doi-asserted-by":"crossref","first-page":"160","DOI":"10.1038\/s41586-024-08334-8","article-title":"Spatial transcriptomic clocks reveal cell proximity effects in brain ageing","volume":"638","author":"Sun","year":"2025","journal-title":"Nature"},{"key":"10.1016\/j.cell.2026.08.032_bib265","doi-asserted-by":"crossref","first-page":"829","DOI":"10.1038\/ncb2765","article-title":"Sequential introduction of reprogramming factors reveals a time-sensitive requirement for individual factors and a sequential EMT\u2013MET mechanism for optimal reprogramming","volume":"15","author":"Liu","year":"2013","journal-title":"Nat. Cell Biol."},{"key":"10.1016\/j.cell.2026.08.032_bib266","doi-asserted-by":"crossref","DOI":"10.1038\/s41467-017-01968-5","article-title":"Integrating evolutionary dynamics into treatment of metastatic castrate-resistant prostate cancer","volume":"8","author":"Zhang","year":"2017","journal-title":"Nat. Commun."},{"key":"10.1016\/j.cell.2026.08.032_bib267","doi-asserted-by":"crossref","first-page":"331","DOI":"10.1111\/1467-9868.00389","article-title":"Optimal Dynamic Treatment Regimes","volume":"65","author":"Murphy","year":"2003","journal-title":"J. R. Stat. Soc. B"},{"key":"10.1016\/j.cell.2026.08.032_bib268","doi-asserted-by":"crossref","first-page":"604","DOI":"10.1038\/s41586-020-03051-4","article-title":"Mastering Atari, Go, chess and shogi by planning with a learned model","volume":"588","author":"Schrittwieser","year":"2020","journal-title":"Nature"},{"key":"10.1016\/j.cell.2026.08.032_bib269","doi-asserted-by":"crossref","first-page":"181","DOI":"10.1016\/S0004-3702(99)00052-1","article-title":"Between MDPs and semi-MDPs: A framework for temporal abstraction in reinforcement learning","volume":"112","author":"Sutton","year":"1999","journal-title":"Artif. Intell."},{"key":"10.1016\/j.cell.2026.08.032_bib270","doi-asserted-by":"crossref","first-page":"26091","DOI":"10.52202\/068431-1892","article-title":"Deep Hierarchical Planning from Pixels","volume":"35","author":"Hafner","year":"2022","journal-title":"Adv. Neural Inf. Process. Syst."}],"container-title":["Cell"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0092867426010056?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0092867426010056?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,9,29]],"date-time":"2026-09-29T04:13:57Z","timestamp":1790655237000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0092867426010056"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,9]]},"references-count":270,"journal-issue":{"issue":"19","published-print":{"date-parts":[[2026,9]]}},"alternative-id":["S0092867426010056"],"URL":"https:\/\/doi.org\/10.1016\/j.cell.2026.08.032","relation":{},"ISSN":["0092-8674"],"issn-type":[{"value":"0092-8674","type":"print"}],"subject":[],"published":{"date-parts":[[2026,9]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"World models for biomedicine","name":"articletitle","label":"Article Title"},{"value":"Cell","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.cell.2026.08.032","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 The Author(s). Published by Elsevier Inc.","name":"copyright","label":"Copyright"}]}}