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Items: 30

1.

Accurate peptide fragmentation predictions allow data driven approaches to replace and improve upon proteomics search engine scoring functions.

Silva ASC, Bouwmeester R, Martens L, Degroeve S.

Bioinformatics. 2019 May 11. pii: btz383. doi: 10.1093/bioinformatics/btz383. [Epub ahead of print]

PMID:
31077310
2.
3.

Comprehensive and Empirical Evaluation of Machine Learning Algorithms for Small Molecule LC Retention Time Prediction.

Bouwmeester R, Martens L, Degroeve S.

Anal Chem. 2019 Mar 5;91(5):3694-3703. doi: 10.1021/acs.analchem.8b05820. Epub 2019 Feb 14.

PMID:
30702864
4.

Data-Driven Rescoring of Metabolite Annotations Significantly Improves Sensitivity.

C Silva AS, Palmer A, Kovalev V, Tarasov A, Alexandrov T, Martens L, Degroeve S.

Anal Chem. 2018 Oct 2;90(19):11636-11642. doi: 10.1021/acs.analchem.8b03224. Epub 2018 Sep 21.

PMID:
30188119
5.

MAPPI-DAT: data management and analysis for protein-protein interaction data from the high-throughput MAPPIT cell microarray platform.

Gupta S, De Puysseleyr V, Van der Heyden J, Maddelein D, Lemmens I, Lievens S, Degroeve S, Tavernier J, Martens L.

Bioinformatics. 2017 May 1;33(9):1424-1425. doi: 10.1093/bioinformatics/btx014.

6.

Identification of Quantitative Proteomic Differences between Mycobacterium tuberculosis Lineages with Altered Virulence.

Peters JS, Calder B, Gonnelli G, Degroeve S, Rajaonarifara E, Mulder N, Soares NC, Martens L, Blackburn JM.

Front Microbiol. 2016 May 31;7:813. doi: 10.3389/fmicb.2016.00813. eCollection 2016.

7.

A Pipeline for Differential Proteomics in Unsequenced Species.

Yılmaz Ş, Victor B, Hulstaert N, Vandermarliere E, Barsnes H, Degroeve S, Gupta S, Sticker A, Gabriël S, Dorny P, Palmblad M, Martens L.

J Proteome Res. 2016 Jun 3;15(6):1963-70. doi: 10.1021/acs.jproteome.6b00140. Epub 2016 May 2.

PMID:
27089233
8.

Designing biomedical proteomics experiments: state-of-the-art and future perspectives.

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.

Expert Rev Proteomics. 2016 May;13(5):495-511. doi: 10.1586/14789450.2016.1172967. Epub 2016 Apr 25. Review.

PMID:
27031651
9.

MS2PIP prediction server: compute and visualize MS2 peak intensity predictions for CID and HCD fragmentation.

Degroeve S, Maddelein D, Martens L.

Nucleic Acids Res. 2015 Jul 1;43(W1):W326-30. doi: 10.1093/nar/gkv542. Epub 2015 May 18.

10.

A decoy-free approach to the identification of peptides.

Gonnelli G, Stock M, Verwaeren J, Maddelein D, De Baets B, Martens L, Degroeve S.

J Proteome Res. 2015 Apr 3;14(4):1792-8. doi: 10.1021/pr501164r. Epub 2015 Mar 6.

PMID:
25714903
11.

Machine learning applications in proteomics research: how the past can boost the future.

Kelchtermans P, Bittremieux W, De Grave K, Degroeve S, Ramon J, Laukens K, Valkenborg D, Barsnes H, Martens L.

Proteomics. 2014 Mar;14(4-5):353-66. doi: 10.1002/pmic.201300289. Epub 2014 Jan 21. Review.

PMID:
24323524
12.

Asn3, a reliable, robust, and universal lock mass for improved accuracy in LC-MS and LC-MS/MS.

Staes A, Vandenbussche J, Demol H, Goethals M, Yilmaz Ş, Hulstaert N, Degroeve S, Kelchtermans P, Martens L, Gevaert K.

Anal Chem. 2013 Nov 19;85(22):11054-60. doi: 10.1021/ac4027093. Epub 2013 Nov 4.

PMID:
24134513
13.

MS2PIP: a tool for MS/MS peak intensity prediction.

Degroeve S, Martens L.

Bioinformatics. 2013 Dec 15;29(24):3199-203. doi: 10.1093/bioinformatics/btt544. Epub 2013 Sep 27.

14.

Proteome-derived peptide libraries to study the substrate specificity profiles of carboxypeptidases.

Tanco S, Lorenzo J, Garcia-Pardo J, Degroeve S, Martens L, Aviles FX, Gevaert K, Van Damme P.

Mol Cell Proteomics. 2013 Aug;12(8):2096-110. doi: 10.1074/mcp.M112.023234. Epub 2013 Apr 25.

15.

Predicting tryptic cleavage from proteomics data using decision tree ensembles.

Fannes T, Vandermarliere E, Schietgat L, Degroeve S, Martens L, Ramon J.

J Proteome Res. 2013 May 3;12(5):2253-9. doi: 10.1021/pr4001114. Epub 2013 Apr 4.

PMID:
23517142
16.

The effect of peptide identification search algorithms on MS2-based label-free protein quantification.

Degroeve S, Staes A, De Bock PJ, Martens L.

OMICS. 2012 Sep;16(9):443-8. doi: 10.1089/omi.2011.0137. Epub 2012 Jul 17.

17.

Towards a human proteomics atlas.

Gonnelli G, Hulstaert N, Degroeve S, Martens L.

Anal Bioanal Chem. 2012 Sep;404(4):1069-77. doi: 10.1007/s00216-012-5940-8. Epub 2012 Mar 25.

PMID:
22447219
18.

Analysis of the resolution limitations of peptide identification algorithms.

Colaert N, Degroeve S, Helsens K, Martens L.

J Proteome Res. 2011 Dec 2;10(12):5555-61. doi: 10.1021/pr200913a. Epub 2011 Oct 26.

PMID:
21995378
19.

Bioinformatics analysis of a Saccharomyces cerevisiae N-terminal proteome provides evidence of alternative translation initiation and post-translational N-terminal acetylation.

Helsens K, Van Damme P, Degroeve S, Martens L, Arnesen T, Vandekerckhove J, Gevaert K.

J Proteome Res. 2011 Aug 5;10(8):3578-89. doi: 10.1021/pr2002325. Epub 2011 Jun 20.

PMID:
21619078
20.

Combining quantitative proteomics data processing workflows for greater sensitivity.

Colaert N, Van Huele C, Degroeve S, Staes A, Vandekerckhove J, Gevaert K, Martens L.

Nat Methods. 2011 Jun;8(6):481-3. doi: 10.1038/nmeth.1604. Epub 2011 May 8.

PMID:
21552256
21.

A posteriori quality control for the curation and reuse of public proteomics data.

Foster JM, Degroeve S, Gatto L, Visser M, Wang R, Griss J, Apweiler R, Martens L.

Proteomics. 2011 Jun;11(11):2182-94. doi: 10.1002/pmic.201000602. Epub 2011 May 2.

PMID:
21538885
22.

A reproducibility-based evaluation procedure for quantifying the differences between MS/MS peak intensity normalization methods.

Degroeve S, Colaert N, Vandekerckhove J, Gevaert K, Martens L.

Proteomics. 2011 Mar;11(6):1172-80. doi: 10.1002/pmic.201000605. Epub 2011 Feb 7.

PMID:
21298791
23.

Translation initiation site prediction on a genomic scale: beauty in simplicity.

Saeys Y, Abeel T, Degroeve S, Van de Peer Y.

Bioinformatics. 2007 Jul 1;23(13):i418-23.

PMID:
17646326
24.

The genome of black cottonwood, Populus trichocarpa (Torr. & Gray).

Tuskan GA, Difazio S, Jansson S, Bohlmann J, Grigoriev I, Hellsten U, Putnam N, Ralph S, Rombauts S, Salamov A, Schein J, Sterck L, Aerts A, Bhalerao RR, Bhalerao RP, Blaudez D, Boerjan W, Brun A, Brunner A, Busov V, Campbell M, Carlson J, Chalot M, Chapman J, Chen GL, Cooper D, Coutinho PM, Couturier J, Covert S, Cronk Q, Cunningham R, Davis J, Degroeve S, Déjardin A, Depamphilis C, Detter J, Dirks B, Dubchak I, Duplessis S, Ehlting J, Ellis B, Gendler K, Goodstein D, Gribskov M, Grimwood J, Groover A, Gunter L, Hamberger B, Heinze B, Helariutta Y, Henrissat B, Holligan D, Holt R, Huang W, Islam-Faridi N, Jones S, Jones-Rhoades M, Jorgensen R, Joshi C, Kangasjärvi J, Karlsson J, Kelleher C, Kirkpatrick R, Kirst M, Kohler A, Kalluri U, Larimer F, Leebens-Mack J, Leplé JC, Locascio P, Lou Y, Lucas S, Martin F, Montanini B, Napoli C, Nelson DR, Nelson C, Nieminen K, Nilsson O, Pereda V, Peter G, Philippe R, Pilate G, Poliakov A, Razumovskaya J, Richardson P, Rinaldi C, Ritland K, Rouzé P, Ryaboy D, Schmutz J, Schrader J, Segerman B, Shin H, Siddiqui A, Sterky F, Terry A, Tsai CJ, Uberbacher E, Unneberg P, Vahala J, Wall K, Wessler S, Yang G, Yin T, Douglas C, Marra M, Sandberg G, Van de Peer Y, Rokhsar D.

Science. 2006 Sep 15;313(5793):1596-604.

25.

Genome analysis of the smallest free-living eukaryote Ostreococcus tauri unveils many unique features.

Derelle E, Ferraz C, Rombauts S, Rouzé P, Worden AZ, Robbens S, Partensky F, Degroeve S, Echeynié S, Cooke R, Saeys Y, Wuyts J, Jabbari K, Bowler C, Panaud O, Piégu B, Ball SG, Ral JP, Bouget FY, Piganeau G, De Baets B, Picard A, Delseny M, Demaille J, Van de Peer Y, Moreau H.

Proc Natl Acad Sci U S A. 2006 Aug 1;103(31):11647-52. Epub 2006 Jul 25.

26.

Large-scale structural analysis of the core promoter in mammalian and plant genomes.

Florquin K, Saeys Y, Degroeve S, Rouzé P, Van de Peer Y.

Nucleic Acids Res. 2005 Jul 27;33(13):4255-64. Print 2005.

27.

SpliceMachine: predicting splice sites from high-dimensional local context representations.

Degroeve S, Saeys Y, De Baets B, Rouzé P, Van de Peer Y.

Bioinformatics. 2005 Apr 15;21(8):1332-8. Epub 2004 Nov 25.

PMID:
15564294
28.

Feature selection for splice site prediction: a new method using EDA-based feature ranking.

Saeys Y, Degroeve S, Aeyels D, Rouzé P, Van de Peer Y.

BMC Bioinformatics. 2004 May 21;5:64.

29.

Fast feature selection using a simple estimation of distribution algorithm: a case study on splice site prediction.

Saeys Y, Degroeve S, Aeyels D, Van De Peer Y, Rouzé P.

Bioinformatics. 2003 Oct;19 Suppl 2:ii179-88.

PMID:
14534188
30.

Feature subset selection for splice site prediction.

Degroeve S, De Baets B, Van de Peer Y, Rouzé P.

Bioinformatics. 2002;18 Suppl 2:S75-83.

PMID:
12385987

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