Handbook of molecular descriptors R Todeschini, V Consonni John Wiley & Sons, 2000 | 5737* | 2000 |
Molecular Descriptors for Chemoinformatics. (2 volumes) R Todeschini, V Consonni Wiley-VCH 41, 1257, 2009 | 2280* | 2009 |
QSAR modeling: where have you been? Where are you going to? A Cherkasov, EN Muratov, D Fourches, A Varnek, II Baskin, M Cronin, ... Journal of medicinal chemistry 57 (12), 4977-5010, 2014 | 1932 | 2014 |
Classification tools in chemistry. Part 1: linear models. PLS-DA D Ballabio, V Consonni Analytical methods 5 (16), 3790-3798, 2013 | 1187 | 2013 |
Dragon software: An easy approach to molecular descriptor calculations A Mauri, V Consonni, M Pavan, R Todeschini Match 56 (2), 237-248, 2006 | 681 | 2006 |
Comments on the Definition of the Q2 Parameter for QSAR Validation V Consonni, D Ballabio, R Todeschini Journal of chemical information and modeling 49 (7), 1669-1678, 2009 | 627 | 2009 |
Structure/response correlations and similarity/diversity analysis by GETAWAY descriptors. 1. Theory of the novel 3D molecular descriptors V Consonni, R Todeschini, M Pavan Journal of chemical information and computer sciences 42 (3), 682-692, 2002 | 568 | 2002 |
Comparison of different approaches to define the applicability domain of QSAR models F Sahigara, K Mansouri, D Ballabio, A Mauri, V Consonni, R Todeschini Molecules 17 (5), 4791-4810, 2012 | 494 | 2012 |
Evaluation of model predictive ability by external validation techniques V Consonni, D Ballabio, R Todeschini Journal of chemometrics 24 (3‐4), 194-201, 2010 | 405 | 2010 |
Structure/response correlations and similarity/diversity analysis by GETAWAY descriptors. 2. Application of the novel 3D molecular descriptors to QSAR/QSPR studies V Consonni, R Todeschini, M Pavan, P Gramatica Journal of chemical information and computer sciences 42 (3), 693-705, 2002 | 382 | 2002 |
New local vertex invariants and molecular descriptors based on functions of the vertex degrees R Todeschini, V Consonni MATCH Commun. Math. Comput. Chem 64 (2), 359-372, 2010 | 291 | 2010 |
Quantitative structure–activity relationship models for ready biodegradability of chemicals K Mansouri, T Ringsted, D Ballabio, R Todeschini, V Consonni Journal of chemical information and modeling 53 (4), 867-878, 2013 | 270 | 2013 |
The K correlation index: theory development and its application in chemometrics R Todeschini, V Consonni, A Maiocchi Chemometrics and Intelligent Laboratory Systems 46 (1), 13-29, 1999 | 235 | 1999 |
Detecting “bad” regression models: multicriteria fitness functions in regression analysis R Todeschini, V Consonni, A Mauri, M Pavan Analytica Chimica Acta 515 (1), 199-208, 2004 | 228 | 2004 |
Modelling and prediction of soil sorption coefficients of non-ionic organic pesticides by molecular descriptors P Gramatica, M Corradi, V Consonni Chemosphere 41 (5), 763-777, 2000 | 224 | 2000 |
Similarity coefficients for binary chemoinformatics data: overview and extended comparison using simulated and real data sets R Todeschini, V Consonni, H Xiang, J Holliday, M Buscema, P Willett Journal of chemical information and modeling 52 (11), 2884-2901, 2012 | 222 | 2012 |
Particle size, chemical composition, seasons of the year and urban, rural or remote site origins as determinants of biological effects of particulate matter on pulmonary cells MG Perrone, M Gualtieri, V Consonni, L Ferrero, G Sangiorgi, E Longhin, ... Environmental pollution 176, 215-227, 2013 | 174 | 2013 |
New spectral indices for molecule description V Consonni, R Todeschini Match 1, 2, 2008 | 150 | 2008 |
CoMPARA: collaborative modeling project for androgen receptor activity K Mansouri, N Kleinstreuer, AM Abdelaziz, D Alberga, VM Alves, ... Environmental Health Perspectives 128 (2), 027002, 2020 | 143 | 2020 |
The Kohonen and CP-ANN toolbox: a collection of MATLAB modules for self organizing maps and counterpropagation artificial neural networks D Ballabio, V Consonni, R Todeschini Chemometrics and intelligent laboratory systems 98 (2), 115-122, 2009 | 137 | 2009 |