Drug response profile-based machine learning enables strategic cell line and compound selection for drug development.
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| Title: | Drug response profile-based machine learning enables strategic cell line and compound selection for drug development. |
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| Authors: | Abdel-Rehim A; Department of Chemical Engineering and Biotechnology, University of Cambridge, Cambridge, CB3 0AS, United Kingdom., Tate E; Arctoris Ltd, Abingdon, OX14 4SA, United Kingdom., Soldatova LN; Department of Mathematics, University College London, London, WC1H 0AY, United Kingdom., King RD; Department of Chemical Engineering and Biotechnology, University of Cambridge, Cambridge, CB3 0AS, United Kingdom.; Department of Biology and Biological Engineering, Chalmers University of Technology, Gothenburg, 412 96, Sweden.; Department of Computer Science and Engineering, Chalmers University of Technology, Gothenburg, 412 96, Sweden.; The Alan Turing Institute, London, NW1 2DB, United Kingdom. |
| Source: | Bioinformatics (Oxford, England) [Bioinformatics] 2026 Jun 01; Vol. 42 (6). |
| Publication Type: | Journal Article |
| Journal Info: | Publisher: Oxford University Press Country of Publication: England NLM ID: 9808944 Publication Model: Print Cited Medium: Internet ISSN: 1367-4811 (Electronic) Linking ISSN: 13674803 NLM ISO Abbreviation: Bioinformatics Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
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| ISSN: | 1367-4811 |
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| DOI: | 10.1093/bioinformatics/btag293 |
