Dose-response modeling in high-throughput cancer drug screenings: an end-to-end approach.
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| Title: | Dose-response modeling in high-throughput cancer drug screenings: an end-to-end approach. |
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| Authors: | Tansey W; Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, NewYork, NY, USA., Li K; Data Science Institute, Columbia University and Columbia University Medical Center, New York, NY, USA and Applied Physics and Applied Mathematics, Columbia University and Columbia University Medical Center, New York, NY, USA., Zhang H; Applied Physics and Applied Mathematics, Columbia University and Columbia University Medical Center, New York, NY, USA., Linderman SW; Data Science Institute, Columbia University and Columbia University Medical Center, New York, NY, USA and Department of Statistics, Columbia University and Columbia University Medical Center, New York, NY, USA., Rabadan R; Department of Systems Biology, Columbia University and Columbia University Medical Center, New York, NY, USA., Blei DM; Data Science Institute, Columbia University and Columbia University Medical Center, New York, NY, USA, Department of Statistics, Columbia University and Columbia University Medical Center, New York, NY, USA and Department of Statistics, Columbia University and Columbia University Medical Center, New York, NY, USA., Wiggins CH; Data Science Institute, Columbia University and Columbia University Medical Center, New York, NY, USA, Department of Applied Physics and Applied Mathematics, Columbia University and Columbia University Medical Center, New York, NY, USA and Department of Systems Biology, Columbia University and Columbia University Medical Center, New York, NY, USA. |
| Source: | Biostatistics (Oxford, England) [Biostatistics] 2022 Apr 13; Vol. 23 (2), pp. 643-665. |
| Publication Type: | Journal Article; Research Support, U.S. Gov't, Non-P.H.S.; Research Support, N.I.H., Extramural; Research Support, Non-U.S. Gov't |
| Journal Info: | Publisher: Oxford University Press Country of Publication: England NLM ID: 100897327 Publication Model: Print Cited Medium: Internet ISSN: 1468-4357 (Electronic) Linking ISSN: 14654644 NLM ISO Abbreviation: Biostatistics Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
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| ISSN: | 1468-4357 |
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| DOI: | 10.1093/biostatistics/kxaa047 |
