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Sven Degroeve - Publications

Affiliations: 
Ghent University, Ghent, Vlaanderen, Belgium 
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43 high-probability publications. We are testing a new system for linking publications to authors. You can help! If you notice any inaccuracies, please sign in and mark papers as correct or incorrect matches. If you identify any major omissions or other inaccuracies in the publication list, please let us know.

Year Citation  Score
2024 Declercq A, Demeulemeester N, Gabriels R, Bouwmeester R, Degroeve S, Martens L. Bioinformatics Pipeline for Processing Single-Cell Data. Methods in Molecular Biology (Clifton, N.J.). 2817: 221-239. PMID 38907156 DOI: 10.1007/978-1-0716-3934-4_15  0.794
2024 Siraj A, Bouwmeester R, Declercq A, Welp L, Chernev A, Wulf A, Urlaub H, Martens L, Degroeve S, Kohlbacher O, Sachsenberg T. Intensity and retention time prediction improves the rescoring of protein-nucleic acid cross-links. Proteomics. 24: e2300144. PMID 38629965 DOI: 10.1002/pmic.202300144  0.772
2024 Bouwmeester R, Richardson K, Denny R, Wilson ID, Degroeve S, Martens L, Vissers JPC. Predicting ion mobility collision cross sections and assessing prediction variation by combining conventional and data driven modeling. Talanta. 274: 125970. PMID 38621320 DOI: 10.1016/j.talanta.2024.125970  0.746
2024 Buur LM, Declercq A, Strobl M, Bouwmeester R, Degroeve S, Martens L, Dorfer V, Gabriels R. MSRescore 3.0 Is a Modular, Flexible, and User-Friendly Platform to Boost Peptide Identifications, as Showcased with MS Amanda 3.0. Journal of Proteome Research. PMID 38491990 DOI: 10.1021/acs.jproteome.3c00785  0.788
2023 Declercq A, Bouwmeester R, Chiva C, Sabidó E, Hirschler A, Carapito C, Martens L, Degroeve S, Gabriels R. Updated MS²PIP web server supports cutting-edge proteomics applications. Nucleic Acids Research. PMID 37140039 DOI: 10.1093/nar/gkad335  0.798
2023 Boone M, Ramasamy P, Zuallaert J, Bouwmeester R, Van Moer B, Maddelein D, Turan D, Hulstaert N, Eeckhaut H, Vandermarliere E, Martens L, Degroeve S, De Neve W, Vranken W, Callewaert N. Author Correction: Massively parallel interrogation of protein fragment secretability using SECRiFY reveals features influencing secretory system transit. Nature Communications. 14: 1072. PMID 36828852 DOI: 10.1038/s41467-023-36844-y  0.736
2023 Neely BA, Dorfer V, Martens L, Bludau I, Bouwmeester R, Degroeve S, Deutsch EW, Gessulat S, Käll L, Palczynski P, Payne SH, Rehfeldt TG, Schmidt T, Schwämmle V, Uszkoreit J, et al. Toward an Integrated Machine Learning Model of a Proteomics Experiment. Journal of Proteome Research. PMID 36744821 DOI: 10.1021/acs.jproteome.2c00711  0.766
2022 Gabriels R, Declercq A, Bouwmeester R, Degroeve S, Martens L. psm_utils: A High-Level Python API for Parsing and Handling Peptide-Spectrum Matches and Proteomics Search Results. Journal of Proteome Research. PMID 36508242 DOI: 10.1021/acs.jproteome.2c00609  0.763
2022 Declercq A, Bouwmeester R, Hirschler A, Carapito C, Degroeve S, Martens L, Gabriels R. MSRescore: Data-driven rescoring dramatically boosts immunopeptide identification rates. Molecular & Cellular Proteomics : McP. 100266. PMID 35803561 DOI: 10.1016/j.mcpro.2022.100266  0.775
2022 Delhaye L, De Bruycker E, Volders PJ, Fijalkowska D, De Sutter D, Degroeve S, Martens L, Mestdagh P, Eyckerman S. Orthogonal proteomics methods to unravel the HOTAIR interactome. Scientific Reports. 12: 1513. PMID 35087108 DOI: 10.1038/s41598-022-05405-6  0.739
2021 Boone M, Ramasamy P, Zuallaert J, Bouwmeester R, Van Moer B, Maddelein D, Turan D, Hulstaert N, Eeckhaut H, Vandermarliere E, Martens L, Degroeve S, De Neve W, Vranken W, Callewaert N. Massively parallel interrogation of protein fragment secretability using SECRiFY reveals features influencing secretory system transit. Nature Communications. 12: 6414. PMID 34741024 DOI: 10.1038/s41467-021-26720-y  0.762
2021 Bouwmeester R, Gabriels R, Hulstaert N, Martens L, Degroeve S. DeepLC can predict retention times for peptides that carry as-yet unseen modifications. Nature Methods. 18: 1363-1369. PMID 34711972 DOI: 10.1038/s41592-021-01301-5  0.772
2021 Van Puyvelde B, Van Uytfanghe K, Tytgat O, Van Oudenhove L, Gabriels R, Bouwmeester R, Daled S, Van Den Bossche T, Ramasamy P, Verhelst S, De Clerck L, Corveleyn L, Willems S, Debunne N, Wynendaele E, ... ... Degroeve S, et al. Cov-MS: A Community-Based Template Assay for Mass-Spectrometry-Based Protein Detection in SARS-CoV-2 Patients. Jacs Au. 1: 750-765. PMID 34254058 DOI: 10.1021/jacsau.1c00048  0.77
2021 Salz R, Bouwmeester R, Gabriels R, Degroeve S, Martens L, Volders PJ, 't Hoen PAC. Personalized Proteome: Comparing Proteogenomics and Open Variant Search Approaches for Single Amino Acid Variant Detection. Journal of Proteome Research. 20: 3353-3364. PMID 33998808 DOI: 10.1021/acs.jproteome.1c00264  0.805
2021 Verbruggen S, Gessulat S, Gabriels R, Matsaroki A, Van de Voorde H, Kuster B, Degroeve S, Martens L, Van Criekinge W, Wilhelm M, Menschaert G. Spectral prediction features as a solution for the search space size problem in proteogenomics. Molecular & Cellular Proteomics : McP. 100076. PMID 33823297 DOI: 10.1016/j.mcpro.2021.100076  0.577
2020 Bouwmeester R, Martens L, Degroeve S. Generalized Calibration Across Liquid Chromatography Setups for Generic Prediction of Small-Molecule Retention Times. Analytical Chemistry. PMID 32281370 DOI: 10.1021/Acs.Analchem.0C00233  0.76
2020 Bouwmeester R, Gabriels R, Bossche TVD, Martens L, Degroeve S. The Age of Data-Driven Proteomics: How Machine Learning Enables Novel Workflows. Proteomics. e1900351. PMID 32267083 DOI: 10.1002/Pmic.201900351  0.787
2020 Van Puyvelde B, Willems S, Gabriels R, Daled S, De Clerck L, Vande Casteele S, Staes A, Impens F, Deforce D, Martens L, Degroeve S, Dhaenens M. Removing the Hidden Data Dependency of DIA with Predicted Spectral Libraries. Proteomics. 20: e1900306. PMID 31981311 DOI: 10.1002/Pmic.201900306  0.612
2020 Van Puyvelde B, Willems S, Gabriels R, Daled S, De Clerck L, Vande Casteele S, Staes A, Impens F, Deforce D, Martens L, Degroeve S, Dhaenens M. Front Cover: Removing the Hidden Data Dependency of DIA with Predicted Spectral Libraries Proteomics. 20: 2070021. DOI: 10.1002/Pmic.202070021  0.536
2019 Silva ASC, Bouwmeester R, Martens L, Degroeve S. Accurate peptide fragmentation predictions allow data driven approaches to replace and improve upon proteomics search engine scoring functions. Bioinformatics (Oxford, England). PMID 31077310 DOI: 10.1093/Bioinformatics/Btz383  0.776
2019 Gabriels R, Martens L, Degroeve S. Updated MS²PIP web server delivers fast and accurate MS² peak intensity prediction for multiple fragmentation methods, instruments and labeling techniques. Nucleic Acids Research. PMID 31028400 DOI: 10.1093/Nar/Gkz299  0.612
2019 Bouwmeester R, Martens L, Degroeve S. Comprehensive and empirical evaluation of machine learning algorithms for small molecule LC retention time prediction. Analytical Chemistry. PMID 30702864 DOI: 10.1021/Acs.Analchem.8B05820  0.764
2018 C Silva AS, Palmer A, Kovalev V, Tarasov A, Alexandrov T, Martens L, Degroeve S. Data-driven rescoring of metabolite annotations significantly improves sensitivity. Analytical Chemistry. PMID 30188119 DOI: 10.1021/Acs.Analchem.8B03224  0.577
2017 Gupta S, De Puysseleyr V, Van der Heyden J, Maddelein D, Lemmens I, Lievens S, Degroeve S, Tavernier J, Martens L. MAPPI-DAT: data management and analysis for protein-protein interaction data from the high-throughput MAPPIT cell microarray platform. Bioinformatics (Oxford, England). 33: 1424-1425. PMID 28453684 DOI: 10.1093/Bioinformatics/Btx014  0.789
2017 Gupta S, De Puysseleyr V, Van der Heyden J, Maddelein D, Lemmens I, Lievens S, Degroeve S, Tavernier J, Martens L. MAPPI-DAT: data management and analysis for protein-protein interaction data from the high-throughput MAPPIT cell microarray platform. Bioinformatics (Oxford, England). PMID 28104627 DOI: 10.1093/bioinformatics/btx014  0.791
2016 Peters JS, Calder B, Gonnelli G, Degroeve S, Rajaonarifara E, Mulder N, Soares NC, Martens L, Blackburn JM. Identification of Quantitative Proteomic Differences between Mycobacterium tuberculosis Lineages with Altered Virulence. Frontiers in Microbiology. 7: 813. PMID 27303394 DOI: 10.3389/Fmicb.2016.00813  0.792
2016 Yılmaz Ş, Victor B, Hulstaert N, Vandermarliere E, Barsnes H, Degroeve S, Gupta S, Sticker A, Gabriël S, Dorny P, Palmblad M, Martens L. A pipeline for differential proteomics in unsequenced species. Journal of Proteome Research. PMID 27089233 DOI: 10.1021/Acs.Jproteome.6B00140  0.758
2016 Maes E, Kelchtermans P, Bittremieux W, De Grave K, Degroeve S, Hooyberghs J, Mertens I, Baggerman G, Ramon J, Laukens K, Martens L, Valkenborg D. Designing biomedical proteomics experiments: state-of-the-art and future perspectives. Expert Review of Proteomics. 13: 495-511. PMID 27031651 DOI: 10.1586/14789450.2016.1172967  0.77
2015 Degroeve S, Maddelein D, Martens L. MS2PIP prediction server: compute and visualize MS2 peak intensity predictions for CID and HCD fragmentation. Nucleic Acids Research. 43: W326-30. PMID 25990723 DOI: 10.1093/Nar/Gkv542  0.796
2015 Gonnelli G, Stock M, Verwaeren J, Maddelein D, De Baets B, Martens L, Degroeve S. A decoy-free approach to the identification of peptides. Journal of Proteome Research. 14: 1792-8. PMID 25714903 DOI: 10.1021/Pr501164R  0.781
2014 Kelchtermans P, Bittremieux W, De Grave K, Degroeve S, Ramon J, Laukens K, Valkenborg D, Barsnes H, Martens L. Machine learning applications in proteomics research: how the past can boost the future. Proteomics. 14: 353-66. PMID 24323524 DOI: 10.1002/Pmic.201300289  0.772
2013 Staes A, Vandenbussche J, Demol H, Goethals M, Yilmaz S, Hulstaert N, Degroeve S, Kelchtermans P, Martens L, Gevaert K. Asn3, a reliable, robust, and universal lock mass for improved accuracy in LC-MS and LC-MS/MS Analytical Chemistry. 85: 11054-11060. PMID 24134513 DOI: 10.1021/Ac4027093  0.776
2013 Degroeve S, Martens L, Jurisica I. MS2PIP: A tool for MS/MS peak intensity prediction Bioinformatics. 29: 3199-3203. PMID 24078703 DOI: 10.1093/Bioinformatics/Btt544  0.628
2013 Tanco S, Lorenzo J, Garcia-Pardo J, Degroeve S, Martens L, Aviles FX, Gevaert K, Van Damme P. Proteome-derived peptide libraries to study the substrate specificity profiles of carboxypeptidases. Molecular & Cellular Proteomics : McP. 12: 2096-110. PMID 23620545 DOI: 10.1074/Mcp.M112.023234  0.571
2013 Fannes T, Vandermarliere E, Schietgat L, Degroeve S, Martens L, Ramon J. Predicting tryptic cleavage from proteomics data using decision tree ensembles. Journal of Proteome Research. 12: 2253-9. PMID 23517142 DOI: 10.7490/F1000Research.1094824.1  0.781
2012 Degroeve S, Staes A, De Bock PJ, Martens L. The effect of peptide identification search algorithms on MS2-based label-free protein quantification. Omics : a Journal of Integrative Biology. 16: 443-8. PMID 22804230 DOI: 10.1089/Omi.2011.0137  0.65
2012 Gonnelli G, Hulstaert N, Degroeve S, Martens L. Towards a human proteomics atlas. Analytical and Bioanalytical Chemistry. 404: 1069-77. PMID 22447219 DOI: 10.1007/S00216-012-5940-8  0.795
2011 Colaert N, Degroeve S, Helsens K, Martens L. Analysis of the resolution limitations of peptide identification algorithms. Journal of Proteome Research. 10: 5555-61. PMID 21995378 DOI: 10.1021/Pr200913A  0.81
2011 Helsens K, Van Damme P, Degroeve S, Martens L, Arnesen T, Vandekerckhove J, Gevaert K. Bioinformatics analysis of a Saccharomyces cerevisiae N-terminal proteome provides evidence of alternative translation initiation and post-translational N-terminal acetylation. Journal of Proteome Research. 10: 3578-89. PMID 21619078 DOI: 10.1021/Pr2002325  0.789
2011 Colaert N, Van Huele C, Degroeve S, Staes A, Vandekerckhove J, Gevaert K, Martens L. Combining quantitative proteomics data processing workflows for greater sensitivity. Nature Methods. 8: 481-3. PMID 21552256 DOI: 10.1038/Nmeth.1604  0.791
2011 Foster JM, Degroeve S, Gatto L, Visser M, Wang R, Griss J, Apweiler R, Martens L. A posteriori quality control for the curation and reuse of public proteomics data. Proteomics. 11: 2182-94. PMID 21538885 DOI: 10.1002/Pmic.201000602  0.591
2011 Degroeve S, Colaert N, Vandekerckhove J, Gevaert K, Martens L. A reproducibility-based evaluation procedure for quantifying the differences between MS/MS peak intensity normalization methods. Proteomics. 11: 1172-80. PMID 21298791 DOI: 10.1002/Pmic.201000605  0.799
2004 Saeys Y, Degroeve S, Aeyels D, Rouzé P, Van de Peer Y. Feature selection for splice site prediction: a new method using EDA-based feature ranking. Bmc Bioinformatics. 5: 64. PMID 15154966 DOI: 10.1186/1471-2105-5-64  0.312
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