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Substituting random forest for multiple linear regression improves binding affinity prediction of scoring functions: Cyscore as a case study
BACKGROUND: State-of-the-art protein-ligand docking methods are generally limited by the traditionally low accuracy of their scoring functions, which are used to predict binding affinity and thus vital for discriminating between active and inactive compounds. Despite intensive research over the year...
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| 主要な著者: | , , , |
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| フォーマット: | Artigo |
| 言語: | Inglês |
| 出版事項: |
BioMed Central
2014
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| 主題: | |
| オンライン･アクセス: | https://ncbi.nlm.nih.gov/pmc/articles/PMC4153907/ https://ncbi.nlm.nih.gov/pubmed/25159129 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1186/1471-2105-15-291 |
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