In Silico Structure-Activity-Relationship (SAR) Models From Machine Learning: A Review
| Xia Ning and George Karypis |
| Drug Development Research, Vol. 72, 2011 |
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| Abstract In this article, we review the recent development for in silico Structure-Activity-Relationship (SAR) models using machine-learning techniques. The review focuses on the following topics: machine-learning algorithms for computational SAR models, single-target-oriented SAR methodologies, Chemogenomics, and future trends. We try to provide the state-of-the-art SAR methods as well as the most up-to-date advancement, in order for the researchers to have a general overview at this area. |
| Research topics: Cheminformatics | Data mining |