| The MicroArray Quality Control (MAQC)-II study of common practices for the development and validation of microarray-based predictive models L Shi, G Campbell, WD Jones, F Campagne, Z Wen, SJ Walker, Z Su, ... Nature biotechnology 28 (8), 827-838, 2010 | 778 | 2010 |
| The concordance between RNA-seq and microarray data depends on chemical treatment and transcript abundance C Wang, B Gong, PR Bushel, J Thierry-Mieg, D Thierry-Mieg, J Xu, ... Nature biotechnology 32 (9), 926-932, 2014 | 556 | 2014 |
| Minerva and minepy: a C engine for the MINE suite and its R, Python and MATLAB wrappers D Albanese, M Filosi, R Visintainer, S Riccadonna, G Jurman, ... Bioinformatics 29 (3), 407-408, 2013 | 243 | 2013 |
| Landscape of conditional eQTL in dorsolateral prefrontal cortex and co-localization with schizophrenia GWAS A Dobbyn, LM Huckins, J Boocock, LG Sloofman, BS Glicksberg, ... The American Journal of Human Genetics 102 (6), 1169-1184, 2018 | 157 | 2018 |
| Canberra distance on ranked lists G Jurman, S Riccadonna, R Visintainer, C Furlanello Proceedings of advances in ranking NIPS 09 workshop, 22-27, 2009 | 143 | 2009 |
| mlpy: Machine learning python D Albanese, R Visintainer, S Merler, S Riccadonna, G Jurman, ... arXiv preprint arXiv:1202.6548, 2012 | 111 | 2012 |
| The HIM glocal metric and kernel for network comparison and classification G Jurman, R Visintainer, M Filosi, S Riccadonna, C Furlanello 2015 IEEE international conference on data science and advanced analytics …, 2015 | 63 | 2015 |
| An introduction to spectral distances in networks G Jurman, R Visintainer, C Furlanello Neural Nets Wirn10, 227-234, 2011 | 55 | 2011 |
| The MAQC-II Project: A comprehensive study of common practices for the development and validation of microarray-based predictive models L Shi, G Campbell, W Jones, F Campagne, Z Wen, S Walker, Z Su, T Chu, ... Nature biotechnology 28 (8), 827-838, 2010 | 49 | 2010 |
| Algebraic comparison of partial lists in bioinformatics G Jurman, S Riccadonna, R Visintainer, C Furlanello PloS one 7 (5), e36540, 2012 | 26 | 2012 |
| Stability indicators in network reconstruction M Filosi, R Visintainer, S Riccadonna, G Jurman, C Furlanello PloS one 9 (2), e89815, 2014 | 25 | 2014 |
| RegnANN: reverse engineering gene networks using artificial neural networks M Grimaldi, R Visintainer, G Jurman PloS one 6 (12), e28646, 2011 | 19 | 2011 |
| The interplay between individual social behavior and clinical symptoms in small clustered groups P Poletti, R Visintainer, B Lepri, S Merler BMC infectious diseases 17, 1-8, 2017 | 14 | 2017 |
| A comprehensive study design reveals treatment-and transcript abundance–dependent concordance between rna-seq and microarray data C Wang, B Gong, PR Bushel, J Thierry-Mieg, D Thierry-Mieg, J Xu, ... Nature biotechnology 32 (9), 926, 2014 | 13 | 2014 |
| DTW-MIC coexpression networks from time-course data S Riccadonna, G Jurman, R Visintainer, M Filosi, C Furlanello PLoS One 11 (3), e0152648, 2016 | 12 | 2016 |
| The HIM glocal metric and kernel for network comparison and classification G Jurman, R Visintainer, M Filosi, S Riccadonna, C Furlanello arXiv preprint arXiv:1201.2931, 2012 | 10 | 2012 |
| A machine learning pipeline for discriminant pathways identification A Barla, G Jurman, R Visintainer, M Squillario, M Filosi, S Riccadonna, ... Computational Intelligence Methods for Bioinformatics and Biostatistics: 8th …, 2012 | 10 | 2012 |
| A glocal distance for network comparison G Jurman, R Visintainer, S Riccadonna, M Filosi, C Furlanello arXiv preprint arXiv:1201.2931, 2012 | 9 | 2012 |
| A minimal PBPK model to accelerate preclinical development of drugs against tuberculosis F Reali, A Fochesato, C Kaddi, R Visintainer, S Watson, M Levi, V Dartois, ... Frontiers in Pharmacology 14, 1272091, 2024 | 7 | 2024 |
| DGW: an exploratory data analysis tool for clustering and visualisation of epigenomic marks S Lukauskas, R Visintainer, G Sanguinetti, GB Schweikert BMC bioinformatics 17, 53-63, 2016 | 7 | 2016 |
