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[摘要]：In-silico tools and computational techniques have become an integral part of pharmaceutical research. These techniques are now used extensively at various phases during the drug development process. Such tools perform a wide range of functions from retrieving and analyzing data to sophisticated computational models for many biological and chemical processes in drug discovery. Among them, machine-learning techniques are becoming especially popular because of their emphasis on obtaining accurate predictions. In this overview, we discuss the increasing role of Machine Learning in Drug Discovery. Since this field has close connections with the field of Statistics, we will first describe similarities and differences between these fields. We will then highlight various domains and problems within drug discovery that are utilizing machine-learning technology to improve and speed up the drug discovery process. Drug Dev Res 72: 112-119, 2011. (C) 2010 Wiley-Liss, Inc. |
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