| The Genome of Black Cottonwood, Populus trichocarpa (Torr. & Gray) GA Tuskan, S Difazio, S Jansson, J Bohlmann, I Grigoriev, U Hellsten, ... science 313 (5793), 1596-1604, 2006 | 4922 | 2006 |
| Genome analysis of the smallest free-living eukaryote Ostreococcus tauri unveils many unique features E Derelle, C Ferraz, S Rombauts, P Rouzé, AZ Worden, S Robbens, ... Proceedings of the National Academy of Sciences 103 (31), 11647-11652, 2006 | 956 | 2006 |
| Random forests as a tool for ecohydrological distribution modelling J Peters, B De Baets, NEC Verhoest, R Samson, S Degroeve, ... ecological modelling 207 (2-4), 304-318, 2007 | 400 | 2007 |
| Feature subset selection for splice site prediction S Degroeve, B De Baets, Y Van de Peer, P Rouzé Bioinformatics 18 (suppl_2), S75-S83, 2002 | 170 | 2002 |
| MS2PIP: a tool for MS/MS peak intensity prediction S Degroeve, L Martens Bioinformatics 29 (24), 3199-3203, 2013 | 147 | 2013 |
| SpliceMachine: predicting splice sites from high-dimensional local context representations S Degroeve, Y Saeys, B De Baets, P Rouzé, Y Van de Peer Bioinformatics 21 (8), 1332-1338, 2005 | 141 | 2005 |
| Large-scale structural analysis of the core promoter in mammalian and plant genomes K Florquin, Y Saeys, S Degroeve, P Rouze, Y Van de Peer Nucleic acids research 33 (13), 4255-4264, 2005 | 139 | 2005 |
| Updated MS²PIP web server delivers fast and accurate MS² peak intensity prediction for multiple fragmentation methods, instruments and labeling techniques R Gabriels, L Martens, S Degroeve Nucleic acids research 47 (W1), W295-W299, 2019 | 94 | 2019 |
| Feature selection for splice site prediction: a new method using EDA-based feature ranking Y Saeys, S Degroeve, D Aeyels, P Rouzé, Y Van de Peer BMC bioinformatics 5, 1-11, 2004 | 89 | 2004 |
| MS2PIP prediction server: compute and visualize MS2 peak intensity predictions for CID and HCD fragmentation S Degroeve, D Maddelein, L Martens Nucleic acids research 43 (W1), W326-W330, 2015 | 80 | 2015 |
| Comprehensive and empirical evaluation of machine learning algorithms for small molecule LC retention time prediction R Bouwmeester, L Martens, S Degroeve Analytical chemistry 91 (5), 3694-3703, 2019 | 79 | 2019 |
| Fast feature selection using a simple estimation of distribution algorithm: a case study on splice site prediction Y Saeys, S Degroeve, D Aeyels, Y Van de Peer, P Rouze Bioinformatics-Oxford 19 (2), 179-188, 2003 | 78 | 2003 |
| Bioinformatics Analysis of a Saccharomyces cerevisiae N-Terminal Proteome Provides Evidence of Alternative Translation Initiation and Post-Translational N … K Helsens, P Van Damme, S Degroeve, L Martens, T Arnesen, ... Journal of proteome research 10 (8), 3578-3589, 2011 | 73 | 2011 |
| Analysis of the resolution limitations of peptide identification algorithms N Colaert, S Degroeve, K Helsens, L Martens Journal of proteome research 10 (12), 5555-5561, 2011 | 70 | 2011 |
| Machine learning applications in proteomics research: How the past can boost the future P Kelchtermans, W Bittremieux, K De Grave, S Degroeve, J Ramon, ... Proteomics 14 (4-5), 353-366, 2014 | 68 | 2014 |
| Translation initiation site prediction on a genomic scale: beauty in simplicity Y Saeys, T Abeel, S Degroeve, Y Van de Peer Bioinformatics 23 (13), i418-i423, 2007 | 67 | 2007 |
| Predicting tryptic cleavage from proteomics data using decision tree ensembles T Fannes, E Vandermarliere, L Schietgat, S Degroeve, L Martens, ... Journal of proteome research 12 (5), 2253-2259, 2013 | 61 | 2013 |
| A decoy-free approach to the identification of peptides G Gonnelli, M Stock, J Verwaeren, D Maddelein, B De Baets, L Martens, ... Journal of proteome research 14 (4), 1792-1798, 2015 | 50 | 2015 |
| Proteome-derived peptide libraries to study the substrate specificity profiles of carboxypeptidases S Tanco, J Lorenzo, J Garcia-Pardo, S Degroeve, L Martens, FX Aviles, ... Molecular & Cellular Proteomics 12 (8), 2096-2110, 2013 | 50 | 2013 |
| An algorithm for detecting and labeling drum events in polyphonic music K Tanghe, S Degroeve, B De Baets Proceedings of the 1st Annual Music Information Retrieval Evaluation …, 2005 | 50 | 2005 |
