| Graph kernels based on tree patterns for molecules P Mahé, JP Vert Machine learning 75 (1), 3-35, 2009 | 315 | 2009 |
| Extensions of marginalized graph kernels P Mahé, N Ueda, T Akutsu, JL Perret, JP Vert Proceedings of the twenty-first international conference on Machine learning, 70, 2004 | 290 | 2004 |
| Graph kernels for molecular structure− activity relationship analysis with support vector machines P Mahé, N Ueda, T Akutsu, JL Perret, JP Vert Journal of chemical information and modeling 45 (4), 939-951, 2005 | 253 | 2005 |
| A fast and agnostic method for bacterial genome-wide association studies: Bridging the gap between k-mers and genetic events M Jaillard, L Lima, M Tournoud, P Mahé, A Van Belkum, V Lacroix, ... PLoS genetics 14 (11), e1007758, 2018 | 211 | 2018 |
| The pharmacophore kernel for virtual screening with support vector machines P Mahé, L Ralaivola, V Stoven, JP Vert Journal of chemical information and modeling 46 (5), 2003-2014, 2006 | 128 | 2006 |
| Large-scale machine learning for metagenomics sequence classification K Vervier, P Mahé, M Tournoud, JB Veyrieras, JP Vert Bioinformatics 32 (7), 1023-1032, 2016 | 101 | 2016 |
| Automatic identification of mixed bacterial species fingerprints in a MALDI-TOF mass-spectrum P Mahe, M Arsac, S Chatellier, V Monnin, N Perrot, S Mailler, V Girard, ... Bioinformatics 30 (9), 1280-1286, 2014 | 97 | 2014 |
| Method for computing similarity between text spans using factored word sequence kernels N Cancedda, P Mahé US Patent 8,077,984, 2011 | 89 | 2011 |
| Predicting bacterial resistance from whole-genome sequences using k-mers and stability selection P Mahé, M Tournoud BMC bioinformatics 19, 1-11, 2018 | 47 | 2018 |
| Digital antimicrobial susceptibility testing using the MilliDrop technology L Jiang, L Boitard, P Broyer, AC Chareire, P Bourne-Branchu, P Mahé, ... European Journal of Clinical Microbiology & Infectious Diseases 35, 415-422, 2016 | 41 | 2016 |
| A large scale evaluation of TBProfiler and Mykrobe for antibiotic resistance prediction in Mycobacterium tuberculosis P Mahé, M El Azami, P Barlas, M Tournoud PeerJ 7, e6857, 2019 | 33 | 2019 |
| Interpreting k-mer–based signatures for antibiotic resistance prediction M Jaillard, M Palmieri, A van Belkum, P Mahé Gigascience 9 (10), giaa110, 2020 | 29 | 2020 |
| Virtual screening with support vector machines and structure kernels P Mahé, JP Vert Combinatorial Chemistry & High Throughput Screening 12 (4), 409-423, 2009 | 20 | 2009 |
| Benchmark of structured machine learning methods for microbial identification from mass-spectrometry data K Vervier, P Mahé, JB Veyrieras, JP Vert arXiv preprint arXiv:1506.07251, 2015 | 17 | 2015 |
| Identification Of Microorganisms By Spectrometry And Structured Classification K Vervier, P Mahe, JB Veyrieras US Patent App. 14/387,777, 2015 | 14 | 2015 |
| Classification of proteomic MS data as Bayesian solution of an inverse problem P Szacherski, JF Giovannelli, L Gerfault, P Mahé, JP Charrier, A Giremus, ... IEEE Access 2, 1248-1262, 2014 | 14 | 2014 |
| MetaVW: Large-scale machine learning for metagenomics sequence classification K Vervier, P Mahé, JP Vert Data Mining for Systems Biology: Methods and Protocols, 9-20, 2018 | 13 | 2018 |
| Noyaux pour graphes et Support Vector Machines pour le criblage virtuel de molécules P Mahé Rapport de stage, DEA MVA 2003, 2002 | 12 | 2002 |
| Factored sequence kernels N Cancedda, P Mahé Neurocomputing 72 (7-9), 1407-1413, 2009 | 11 | 2009 |
| Kernel design for virtual screening of small molecules with support vector machines P Mahe PhD thesis, Ecole des Mines de Paris, 2006 | 11 | 2006 |
