Kunal Roy
Researcher Next ID · RN-037479
Researcher · Biochemistry, Genetics and Molecular Biology
Mohali, India
- Works count
- 670
- Citation count
- 20,258
- H-index
- 63
- i10-index
- 333
Research interests
Publications
Prediction reliability of QSAR models: an overview of various validation tools
Archives of Toxicology · 2022 · https://doi.org/10.1007/s00204-022-03252-y
Green Chemistry in the Synthesis of Pharmaceuticals
Chemical Reviews · 2021 · https://doi.org/10.1021/acs.chemrev.1c00631
Be aware of error measures. Further studies on validation of predictive QSAR models
Chemometrics and Intelligent Laboratory Systems · 2016 · https://doi.org/10.1016/j.chemolab.2016.01.008
“NanoBRIDGES” software: Open access tools to perform QSAR and nano-QSAR modeling
Chemometrics and Intelligent Laboratory Systems · 2015 · https://doi.org/10.1016/j.chemolab.2015.07.007
On a simple approach for determining applicability domain of QSAR models
Chemometrics and Intelligent Laboratory Systems · 2015 · https://doi.org/10.1016/j.chemolab.2015.04.013
A Primer on QSAR/QSPR Modeling
Springer briefs in molecular science · 2015 · https://doi.org/10.1007/978-3-319-17281-1
Some case studies on application of “ r m 2 ” metrics for judging quality of quantitative structure–activity relationship predictions: Emphasis on scaling of response data
Journal of Computational Chemistry · 2013 · https://doi.org/10.1002/jcc.23231
Comparative Studies on Some Metrics for External Validation of QSPR Models
Journal of Chemical Information and Modeling · 2011 · https://doi.org/10.1021/ci200520g
On Various Metrics Used for Validation of Predictive QSAR Models with Applications in Virtual Screening and Focused Library Design
Combinatorial Chemistry & High Throughput Screening · 2011 · https://doi.org/10.2174/138620711795767893
Further exploring r metrics for validation of QSPR models
Chemometrics and Intelligent Laboratory Systems · 2011 · https://doi.org/10.1016/j.chemolab.2011.03.011
Comparative QSARs for antimalarial endochins: Importance of descriptor-thinning and noise reduction prior to feature selection
Chemometrics and Intelligent Laboratory Systems · 2011 · https://doi.org/10.1016/j.chemolab.2011.08.007
Exploring quantitative structure–activity relationship studies of antioxidant phenolic compounds obtained from traditional Chinese medicinal plants
Molecular Simulation · 2010 · https://doi.org/10.1080/08927022.2010.503326
On Two Novel Parameters for Validation of Predictive QSAR Models
Molecules · 2009 · https://doi.org/10.3390/molecules14051660
On some aspects of validation of predictive quantitative structure–activity relationship models
Expert Opinion on Drug Discovery · 2007 · https://doi.org/10.1517/17460441.2.12.1567
On Some Aspects of Variable Selection for Partial Least Squares Regression Models
QSAR & Combinatorial Science · 2007 · https://doi.org/10.1002/qsar.200710043
Exploring the impact of size of training sets for the development of predictive QSAR models
Chemometrics and Intelligent Laboratory Systems · 2007 · https://doi.org/10.1016/j.chemolab.2007.07.004
On Selection of Training and Test Sets for the Development of Predictive QSAR models
QSAR & Combinatorial Science · 2005 · https://doi.org/10.1002/qsar.200510161
Current projects
No projects listed.