Combinatorial prediction of therapeutic perturbations using causally inspired neural networks.

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Title: Combinatorial prediction of therapeutic perturbations using causally inspired neural networks.
Authors: Gonzalez G; Imperial College London, London, UK.; F. Hoffmann-La Roche Ltd, Basel, Switzerland.; Prescient Design, Genentech, South San Francisco, CA, USA., Lin X; Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA., Herath I; Merck & Co., South San Francisco, CA, USA.; Cornell University, Ithaca, NY, USA.; University of Pittsburgh School of Medicine-Carnegie Mellon University, Pittsburgh, PA, USA., Veselkov K; Imperial College London, London, UK.; Yale School of Public Health, New Haven, CT, USA., Bronstein M; University of Oxford, Oxford, UK.; AITHYRA, Vienna, Austria., Zitnik M; Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA. marinka@hms.harvard.edu.; Kempner Institute for the Study of Natural and Artificial Intelligence, Harvard University, Cambridge, MA, USA. marinka@hms.harvard.edu.; Broad Institute of MIT and Harvard, Cambridge, MA, USA. marinka@hms.harvard.edu.; Harvard Data Science Initiative, Cambridge, MA, USA. marinka@hms.harvard.edu.
Source: Nature biomedical engineering [Nat Biomed Eng] 2026 May; Vol. 10 (5), pp. 1008-1025. Date of Electronic Publication: 2025 Sep 09.
Publication Type: Journal Article
Journal Info: Publisher: Springer Nature Country of Publication: England NLM ID: 101696896 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 2157-846X (Electronic) Linking ISSN: 2157846X NLM ISO Abbreviation: Nat Biomed Eng Subsets: MEDLINE
Database: MEDLINE Ultimate
Description
ISSN:2157-846X
DOI:10.1038/s41551-025-01481-x