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BMC Research Notes|December 5, 2015
Enzyme mechanism prediction: a template matching problem on InterPro signature subspacesHamse Y Mussa, Luna De Ferrari, John B O MitchellJournal of Cheminformatics|December 3, 2015
A note on utilising binary features as ligand descriptorsHamse Y Mussa, John B O Mitchell, Robert C GlenPattern Recognition Letters|October 6, 2015
The Parzen Window method: In terms of two vectors and one matrixHamse Y Mussa, John B O Mitchell, Avid M AfzalJournal of Cheminformatics|June 16, 2015
Verifying the fully "Laplacianised" posterior Naïve Bayesian approach and moreHamse Y Mussa, David Marcus, John B O Mitchell, et al.Journal of Chemical Information and Modeling|June 24, 2011
Classifying molecules using a sparse probabilistic kernel binary classifierRobert Lowe, Hamse Y Mussa, John B O Mitchell, et al.BMC Bioinformatics|June 3, 2014
From sequence to enzyme mechanism using multi-label machine learningLuna De Ferrari, John B O MitchellEvolutionary Bioinformatics Online|January 8, 2016
Why do Sequence Signatures Predict Enzyme Mechanism? Homology versus ChemistryKirsten E Beattie, Luna De Ferrari, John B O MitchellJournal of Chemical Information and Modeling|July 9, 2013
In silico target predictions: defining a benchmarking data set and comparison of performance of the multiclass Naïve Bayes and Parzen-Rosenblatt windowAlexios Koutsoukas, Robert Lowe, Yasaman Kalantarmotamedi, et al.IEEE Transactions on Neural Networks|March 3, 2010
Memory-efficient fully coupled filtering approach for observational model buildingHamse Y Mussa, Robert C GlenJournal of Chemical Information and Modeling|February 26, 2014
Uniting cheminformatics and chemical theory to predict the intrinsic aqueous solubility of crystalline druglike moleculesJames L McDonagh, Neetika Nath, Luna De Ferrari, et al.Pageof 10