| The advantages of the Matthews correlation coefficient (MCC) over F1 score and accuracy in binary classification evaluation D Chicco, G Jurman BMC genomics 21 (1), 1-13, 2020 | 3441 | 2020 |
| A promoter-level mammalian expression atlas Nature 507 (7493), 462-470, 2014 | 1644 | 2014 |
| The coefficient of determination R-squared is more informative than SMAPE, MAE, MAPE, MSE and RMSE in regression analysis evaluation D Chicco, MJ Warrens, G Jurman PeerJ Computer Science 7, e623, 2021 | 1353 | 2021 |
| The MicroArray Quality Control (MAQC)-II study of common practices for the development and validation of microarray-based predictive models Nature biotechnology 28 (8), 827-838, 2010 | 866 | 2010 |
| Repeatability of published microarray gene expression analyses JPA Ioannidis, DB Allison, CA Ball, I Coulibaly, X Cui, AC Culhane, ... Nature genetics 41 (2), 149-155, 2009 | 641 | 2009 |
| A comparison of MCC and CEN error measures in multi-class prediction G Jurman, S Riccadonna, C Furlanello PloS one 7 (8), e41882, 2012 | 539 | 2012 |
| The Matthews correlation coefficient (MCC) is more reliable than balanced accuracy, bookmaker informedness, and markedness in two-class confusion matrix evaluation D Chicco, N Tötsch, G Jurman BioData mining 14 (1), 1-22, 2021 | 495 | 2021 |
| 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 | 492 | 2014 |
| Machine learning can predict survival of patients with heart failure from serum creatinine and ejection fraction alone D Chicco, G Jurman BMC medical informatics and decision making 20 (1), 1-16, 2020 | 422 | 2020 |
| 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, bts707, 2012 | 203 | 2012 |
| Entropy-based gene ranking without selection bias for the predictive classification of microarray data C Furlanello, M Serafini, S Merler, G Jurman BMC bioinformatics 4 (1), 1-20, 2003 | 183 | 2003 |
| The Matthews correlation coefficient (MCC) is more informative than Cohen’s Kappa and Brier score in binary classification assessment D Chicco, MJ Warrens, G Jurman IEEE Access 9, 78368-78381, 2021 | 169 | 2021 |
| Differential roles of epigenetic changes and Foxp3 expression in regulatory T cell-specific transcriptional regulation H Morikawa, N Ohkura, A Vandenbon, M Itoh, S Nagao-Sato, H Kawaji, ... Proceedings of the National Academy of Sciences 111 (14), 5289-5294, 2014 | 130 | 2014 |
| Canberra distance on ranked lists G Jurman, S Riccadonna, R Visintainer, C Furlanello Proceedings of advances in ranking NIPS 09 workshop, 22-27, 2009 | 127 | 2009 |
| Algebraic stability indicators for ranked lists in molecular profiling G Jurman, S Merler, A Barla, S Paoli, A Galea, C Furlanello Bioinformatics 24 (2), 258-264, 2008 | 125 | 2008 |
| mlpy: Machine learning Python D Albanese, R Visintainer, S Merler, S Riccadonna, G Jurman, ... arXiv preprint arXiv:1202.6548, 2012 | 105 | 2012 |
| Clinical value of prognosis gene expression signatures in colorectal cancer: a systematic review R Sanz-Pamplona, A Berenguer, D Cordero, S Riccadonna, X Sole, ... PloS one 7 (11), e48877, 2012 | 104 | 2012 |
| An accelerated procedure for recursive feature ranking on microarray data C Furlanello, M Serafini, S Merler, G Jurman Neural Networks 16 (5-6), 641-648, 2003 | 101 | 2003 |
| Phylogenetic convolutional neural networks in metagenomics D Fioravanti, Y Giarratano, V Maggio, C Agostinelli, M Chierici, G Jurman, ... BMC bioinformatics 19, 1-13, 2018 | 98 | 2018 |
| PD-L1 is a therapeutic target of the bromodomain inhibitor JQ1 and, combined with HLA class I, a promising prognostic biomarker in neuroblastoma O Melaiu, M Mina, M Chierici, R Boldrini, G Jurman, P Romania, ... Clinical Cancer Research 23 (15), 4462-4472, 2017 | 95 | 2017 |
Cesare FurlanelloHK3 Lab (Rovereto, Italy) & LIGHT Center (Brescia, Italy)Verified email at hk3lab.ai
