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Journal of Chemical Information and Computer Sciences|July 27, 2004
Development of QSAR models to predict and interpret the biological activity of artemisinin analoguesRajarshi Guha, Peter C JursJournal of Chemical Information and Computer Sciences|November 24, 2004
Development of linear, ensemble, and nonlinear models for the prediction and interpretation of the biological activity of a set of PDGFR inhibitorsRajarshi Guha, Peter C JursJournal of Chemical Information and Modeling|June 1, 2005
Interpreting computational neural network QSAR models: a measure of descriptor importanceRajarshi Guha, Peter C JursJournal of Chemical Information and Modeling|January 26, 2005
Determining the validity of a QSAR model--a classification approachRajarshi Guha, Peter C JursJournal of Molecular Graphics & Modelling|August 28, 2004
Generation of QSAR sets with a self-organizing mapRajarshi Guha, Jon R Serra, Peter C JursJournal of Chemical Information and Modeling|July 28, 2005
Interpreting computational neural network quantitative structure-activity relationship models: a detailed interpretation of the weights and biasesRajarshi Guha, David T Stanton, Peter C JursJournal of Chemical Information and Modeling|January 24, 2006
Scalable partitioning and exploration of chemical spaces using geometric hashingDebojyoti Dutta, Rajarshi Guha, Peter C Jurs, et al.Journal of Chemical Information and Modeling|July 25, 2006
Local lazy regression: making use of the neighborhood to improve QSAR predictionsRajarshi Guha, Debojyoti Dutta, Peter C Jurs, et al.Journal of Chemical Information and Modeling|July 25, 2006
R-NN curves: an intuitive approach to outlier detection using a distance based methodRajarshi Guha, Debojyoti Dutta, Peter C Jurs, et al.Methods in Molecular Biology (Clifton, N.J.)|September 15, 2010
The ups and downs of structure-activity landscapesRajarshi GuhaPageof 15