| Classification of drugs in absorption classes using the classification and regression trees (CART) methodology E Deconinck, T Hancock, D Coomans, DL Massart, Y Vander Heyden Journal of Pharmaceutical and Biomedical Analysis 39 (1-2), 91-103, 2005 | 163 | 2005 |
| A performance comparison of modern statistical techniques for molecular descriptor selection and retention prediction in chromatographic QSRR studies T Hancock, R Put, D Coomans, Y Vander Heyden, Y Everingham Chemometrics and Intelligent Laboratory Systems 76 (2), 185-196, 2005 | 155 | 2005 |
| Computational recognition for long non-coding RNA (lncRNA): Software and databases S Yotsukura, D duVerle, T Hancock, Y Natsume-Kitatani, H Mamitsuka Briefings in bioinformatics 18 (1), 9-27, 2017 | 47 | 2017 |
| Mining metabolic pathways through gene expression T Hancock, I Takigawa, H Mamitsuka Bioinformatics 26 (17), 2128-2135, 2010 | 29 | 2010 |
| Putative bovine topological association domains and CTCF binding motifs can reduce the search space for causative regulatory variants of complex traits M Wang, TP Hancock, AJ Chamberlain, CJ Vander Jagt, JE Pryce, ... BMC genomics 19, 1-17, 2018 | 27 | 2018 |
| Putative enhancer sites in the bovine genome are enriched with variants affecting complex traits M Wang, TP Hancock, IM MacLeod, JE Pryce, BG Cocks, BJ Hayes Genetics Selection Evolution 49, 1-16, 2017 | 25 | 2017 |
| Adaptive wavelet modelling of a nested 3 factor experimental design in NIR chemometrics D Donald, D Coomans, Y Everingham, D Cozzolino, M Gishen, ... Chemometrics and intelligent laboratory systems 82 (1-2), 122-129, 2006 | 25 | 2006 |
| Bagged super wavelets reduction for boosted prostate cancer classification of seldi-tof mass spectral serum profiles D Donald, T Hancock, D Coomans, Y Everingham Chemometrics and intelligent laboratory systems 82 (1-2), 2-7, 2006 | 23 | 2006 |
| Auto-associative multivariate regression trees for cluster analysis C Smyth, D Coomans, Y Everingham, T Hancock Chemometrics and Intelligent Laboratory Systems 80 (1), 120-129, 2006 | 18 | 2006 |
| Boosted network classifiers for local feature selection T Hancock, H Mamitsuka IEEE transactions on neural networks and learning systems 23 (11), 1767-1778, 2012 | 17 | 2012 |
| NetPathMiner: R/Bioconductor package for network path mining through gene expression A Mohamed, T Hancock, CH Nguyen, H Mamitsuka Bioinformatics 30 (21), 3139-3141, 2014 | 16 | 2014 |
| Supervised hierarchical clustering using CART TP Hancock, DH Coomans, YL Everingham Proceedings of MODSIM 2003 International Congress on Modelling and …, 2003 | 14 | 2003 |
| Identifying neighborhoods of coordinated gene expression and metabolite profiles T Hancock, N Wicker, I Takigawa, H Mamitsuka PLoS One 7 (2), e31345, 2012 | 12 | 2012 |
| Unsupervised data mining: introduction D Coomans, C Smyth, I Lee, T Hancock, J Yang Elsevier 2, 559-576, 2009 | 11 | 2009 |
| A markov classification model for metabolic pathways T Hancock, H Mamitsuka Algorithms for Molecular Biology 5, 1-9, 2010 | 10 | 2010 |
| A toolbox approach to flexible and efficient data mining OM Nielsen⋆, P Christen, M Hegland, T Semenova, T Hancock Advances in Knowledge Discovery and Data Mining: 5th Pacific-Asia Conference …, 2001 | 9 | 2001 |
| Reliabilities of Australian dairy genomic breeding values increase through the addition of genotyped females with excellent phenotypes. JE Pryce, P Douglas, CM Reich, AJ Chamberlain, PJ Bowman, ... | 7 | 2017 |
| Nuclear magnetic resonance metabonomic profiling using tO2PLS GM Kirwan, T Hancock, K Hassell, JO Niere, D Nugegoda, S Goto, ... Analytica Chimica Acta 781, 33-40, 2013 | 6 | 2013 |
| Implementation of multiple traits multi lactation random regression test day model for production traits in Australia K Konstantinov Interbull Bulletin, 2015 | 5 | 2015 |
| A markov classification model for metabolic pathways T Hancock, H Mamitsuka International Workshop on Algorithms in Bioinformatics, 121-132, 2009 | 5 | 2009 |
Ichigaku TakigawaKyoto University / Hokkaido UniversityVerified email at kyoto-u.ac.jp