Prediction of Synergism from Chemical-Genetic Interactions by Machine Learning.

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第一作者： Jan,Wildenhain

第一单位： Wellcome Trust Centre for Cell Biology, School of Biological Sciences, University of Edinburgh, Edinburgh EH9 3JR, UK.

作者： Jan,Wildenhain ^[1] ; Michaela,Spitzer ^[2] ; Sonam,Dolma ^[3] ; Nick,Jarvik ^[3] ; Rachel,White ^[1] ; Marcia,Roy ^[1] ; Emma,Griffiths ^[4] ; David S,Bellows ^[3] ; Gerard D,Wright ^[4] ; Mike,Tyers ^[5]

作者单位： Wellcome Trust Centre for Cell Biology, School of Biological Sciences, University of Edinburgh, Edinburgh EH9 3JR, UK. ^[1] Wellcome Trust Centre for Cell Biology, School of Biological Sciences, University of Edinburgh, Edinburgh EH9 3JR, UK; Michael G. DeGroote Institute for Infectious Disease Research, McMaster University, Hamilton, ON L8N 3Z5, Canada. ^[2] Lunenfeld-Tanenbaum Research Institute, Mount Sinai Hospital, Toronto, ON M5G 1X5, Canada. ^[3] Michael G. DeGroote Institute for Infectious Disease Research, McMaster University, Hamilton, ON L8N 3Z5, Canada. ^[4] Wellcome Trust Centre for Cell Biology, School of Biological Sciences, University of Edinburgh, Edinburgh EH9 3JR, UK; Institute for Research in Immunology and Cancer, Department of Medicine, Université de Montréal, Montréal, QC H3C 3J7, Canada. Electronic address: md.tyers@umontreal.ca. ^[5]

关键词 Bayesian analysis antifungal bipartite graph chemical-genetic interaction combination genetic network machine learning random forest synergism

DOI 10.1016/j.cels.2015.12.003

PMID 27136353

发布时间 2022-01-31

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Cell systems

2015年1卷6期

383-95页

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Prediction of Synergism from Chemical-Genetic Interactions by Machine Learning.

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Prediction of Synergism from Chemical-Genetic Interactions by Machine Learning.

Cell systems

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Cell systems

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