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Automatic Quantitative Structure-Activity Relationship Modeling to Fill Data Gaps in High-Throughput Screening.

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Title: Automatic Quantitative Structure-Activity Relationship Modeling to Fill Data Gaps in High-Throughput Screening.
Authors: Ciallella HL; Center for Computational and Integrative Biology, Rutgers University, Camden, NJ, USA., Chung E; Center for Computational and Integrative Biology, Rutgers University, Camden, NJ, USA., Russo DP; Center for Computational and Integrative Biology, Rutgers University, Camden, NJ, USA.; Department of Chemistry, Rutgers University, Camden, NJ, USA., Zhu H; Center for Computational and Integrative Biology, Rutgers University, Camden, NJ, USA. hao.zhu99@rutgers.edu.; Department of Chemistry, Rutgers University, Camden, NJ, USA. hao.zhu99@rutgers.edu.
Source: Methods in molecular biology (Clifton, N.J.) [Methods Mol Biol] 2022; Vol. 2474, pp. 169-187.
Publication Type: Journal Article
Journal Info: Publisher: Humana Press Country of Publication: United States NLM ID: 9214969 Publication Model: Print Cited Medium: Internet ISSN: 1940-6029 (Electronic) Linking ISSN: 10643745 NLM ISO Abbreviation: Methods Mol Biol Subsets: MEDLINE
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