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A new open source data analysis python script for QSAR study and its validation

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dc.contributor.author Jadhav, Hemant R.
dc.date.accessioned 2023-11-30T07:22:45Z
dc.date.available 2023-11-30T07:22:45Z
dc.date.issued 2014-09
dc.identifier.uri https://link.springer.com/article/10.1007/s00044-014-1240-5
dc.identifier.uri http://dspace.bits-pilani.ac.in:8080/xmlui/handle/123456789/13282
dc.description.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. en_US
dc.language.iso en en_US
dc.publisher Springer en_US
dc.subject Pharmacy en_US
dc.subject Quantitative structure–activity relationship (QSAR) en_US
dc.subject QSAR en_US
dc.title A new open source data analysis python script for QSAR study and its validation en_US
dc.type Article en_US


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