Publications
Ballester, P.J., Schreyer, A. and Blundell, T.L. (2014):'Does a More Precise Chemical Description of Protein−Ligand Complexes Lead to More Accurate Prediction of Binding Affinity?' Journal of Chemical Information and Modeling [PDF]
Menden, M.P., Iorio, F., Garnett, M., McDermott, U., Benes, C.H., Ballester, P.J. and Saez-Rodriguez, J. (2014): 'Machine Learning Prediction of Cancer Cell Sensitivity to Drugs Based on Genomic and Chemical Properties.' PLoS One [PDF]
Ballester, P.J., Mangold, M., Howard, N.I., Marchese-Robinson, R.L., Abell, C., Blumberger, J. and Mitchell, J.B.O. (2012): `Hierarchical virtual screening for the discovery of new molecular scaffolds in antibacterial hit identification’. Journal of the Royal Society Interface [PDF]
Ballester, P.J. and Mitchell, J.B.O. (2011): ‘Comments on "Leave-Cluster-Out Cross-Validation is appropriate for scoring functions derived from diverse protein data sets": significance for the validation of scoring functions’. Journal of Chemical Information and Modeling 51 (8), 1739–1741 [PDF]
Ballester, P.J. (2011): 'Ultrafast shape recognition: method and applications'. Future Medicinal Chemistry 3, 65-78 [PDF][PREPRINT]
Ballester, P.J. and Mitchell, J.B.O. (2010): ‘A machine learning approach to predicting protein-ligand binding affinity with applications to molecular docking’. Bioinformatics 26 (9), 1169-1175 [PDF][SD]
Ballester, P.J., Westwood, I., Laurieri, N., Sim, E. and Richards, W.G. (2010): 'Prospective virtual screening with Ultrafast Shape Recognition: the identification of novel inhibitors of arylamine N-acetyltransferases'. Journal of The Royal Society Interface 7, 335-342 [PDF][SD]
Ballester, P.J. and Richards, W.G. (2007): 'Ultrafast Shape Recognition for Similarity Search in Molecular Databases'. Proceedings of the Royal Society A 463, 1307-1321 [PDF]
