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Please use this identifier to cite or link to this item: http://dspace.bits-pilani.ac.in:8080/jspui/xmlui/handle/123456789/13282
Title: A new open source data analysis python script for QSAR study and its validation
Authors: Jadhav, Hemant R.
Keywords: Pharmacy
Quantitative structure–activity relationship (QSAR)
QSAR
Issue Date: Sep-2014
Publisher: Springer
Abstract: Quantitative structure–activity relationship (QSAR) is the statistical correlation of physicochemical properties of the structure with biological activity. QSAR study involves two main steps: first is the generation of descriptors, and second is building and validating the models. We have developed a python script that effectively uses descriptor and activity data in building and validating best QSAR model. Although available software provides descriptor calculation, lack of either the components needed for cross-validation or proper workflow for QSAR analysis is the bottleneck. In this paper we report, the validation results of this software using data available for MMP 13 inhibitors and anti-malarial compounds. We have found that the values obtained using this script correlate well with that calculated from Microsoft excel and reported QSAR models.
URI: https://link.springer.com/article/10.1007/s00044-014-1240-5
http://dspace.bits-pilani.ac.in:8080/xmlui/handle/123456789/13282
Appears in Collections:Department of Pharmacy

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