Abdo, Ammar and Salim, Naomie (2008) Similarity-based virtual screening with a bayesian inference network. ChemMedChem, 3 . pp. 1-10. ISSN 1860-7179 (Print) 1860-7187 (Electronic)
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Official URL: http://www.ncbi.nlm.nih.gov/pubmed/19072820
Many methods have been developed to capture the biological similarity between two compounds for use in drug discovery. A variety of similarity metrics have been introduced, the Tanimoto coefficient being the most prominent. Many of the approaches assume that molecular features or descriptors that do not relate to the biological activity carry the same weight as the important aspects in terms of biological similarity. Herein, a novel similarity searching approach using a Bayesian inference network is discussed. Similarity searching is regarded as an inference or evidential reasoning process in which the probability that a given compound has biological similarity with the query is estimated and used as evidence. Our experiments demonstrate that the similarity approach based on Bayesian inference networks is likely to outperform the Tanimoto similarity search and offer a promising alternative to existing similarity search approaches.
|Uncontrolled Keywords:||biological, Tanimoto, descriptors, Bayesian inference|
|Subjects:||Q Science > QA Mathematics > QA75 Electronic computers. Computer science|
|Divisions:||Computer Science and Information System (Formerly known)|
|Deposited By:||Norshiela Buyamin|
|Deposited On:||06 May 2009 04:35|
|Last Modified:||06 May 2009 04:35|
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