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An enhancement of Bayesian inference network for ligand-based virtual screening using minifingerprints

Ahmed, Ali and Abdoand, Ammar and Salim, Naomie (2012) An enhancement of Bayesian inference network for ligand-based virtual screening using minifingerprints. In: Fourth International Conference on Machine Vision (ICMV 2011): Computer Vision and Image Analysis: Pattern Recognition and Basic Technologies. Society of Photo-Optical Instrumentation Engineers (SPIE)., Bellingham, USA. ISBN 978-081949026-1

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Official URL: http://dx.doi.org/10.1117/12.920338

Abstract

Selection and identification of a subset of compounds from libraries or databases, which are likely to possess a desired biological activity is the main target of ligand-based virtual screening approaches. The main challenge of such approaches is achieving of high recall of active molecules. To this end, different models of Bayesian network have been developed. In this study, we enhance the Bayesian Inference Network (BIN) using a subset of selected molecule's features. In this approach, a few features that represent the Minifingerprints (MFPs) were filtered from the molecular fingerprint features based on an analysis of distributions of molecular descriptors and structural fragments into large compound data set collections. Simulated virtual screening experiments with MDL Drug Data Report (MDDR) data sets showed that the proposed method provides simple ways of enhancing the cost effectiveness of ligand-based virtual screening searches, especially for higher diversity data set.

Item Type:Book Section
Additional Information:Indexed by Scopus
Uncontrolled Keywords:Bayesian Inference Network (BIN), Features selection, fingerprint features, High-Throughput Screening (HTS), Minifingerprints, Quantitative Structure-Activity Relationships (QSAR), similarity search, virtual screening
Subjects:Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions:Computer Science and Information System
ID Code:34274
Deposited By:INVALID USER
Deposited On:30 Sep 2013 07:41
Last Modified:17 Sep 2017 00:28

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