Matthew The - Google Scholar Citations

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	All	Since 2014
Citations	72	72
h-index	4	4
i10-index	3	3

20162017201820193 11 31 25

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Lukas KällProfessor, KTH Royal Institute of Technology, Science for Life LaboratoryVerified email at kth.se
William Stafford NobleProfessor of Genome Sciences, University of WashingtonVerified email at uw.edu
Yasset Perez-RiverolTeam Coordinator, Proteomics Resources, EMBL-EBI, UKVerified email at ebi.ac.uk
Michael MacCossProfessor of Genome Sciences, University of WashingtonVerified email at uw.edu
Michael R. HoopmannInstitute for Systems BiologyVerified email at systemsbiology.org
Magnus PalmbladLeiden University Medical CenterVerified email at lumc.nl
Samuel H PayneAssociate Professor, Brigham Young UniversityVerified email at byu.edu
Fredrik EdforsStanford, Department of GeneticsVerified email at scilifelab.se
Juan Antonio VizcainoProteomics Team Leader, EMBL-EBIVerified email at ebi.ac.uk
Johannes GrissPostDoc, EMBL-European Biofinformatics InstitueVerified email at ebi.ac.uk
Heydar Maboudi AfkhamKTHVerified email at kth.se
Christopher M. ColangeloPrimary Ion, LLCVerified email at primaryion.com
Ryan WilsonUniversity of WashingtonVerified email at uw.edu
Hyungwon ChoiNational University of SingaporeVerified email at nus.edu.sg
Henry LamHong Kong University of Science and Technology OR Massachusetts Institute of Technology OR InstituteVerified email at ust.hk
Joon-Yong LeeScientist, BSD, PNNLVerified email at pnnl.gov

Matthew The

KTH Royal Institute of Technology

Verified email at kth.se - Homepage

Bioinformatics Machine learning


Title	Cited by	Year
Fast and accurate protein false discovery rates on large-scale proteomics data sets with percolator 3.0 M The, MJ MacCoss, WS Noble, L Käll Journal of The American Society for Mass Spectrometry 27 (11), 1719-1727, 2016	31	2016
How to talk about protein‐level false discovery rates in shotgun proteomics M The, A Tasnim, L Käll Proteomics 16 (18), 2461-2469, 2016	17	2016
MaRaCluster: A fragment rarity metric for clustering fragment spectra in shotgun proteomics M The, L Käll Journal of proteome research 15 (3), 713-720, 2016	12	2016
A protein standard that emulates homology for the characterization of protein inference algorithms M The, F Edfors, Y Perez-Riverol, SH Payne, MR Hoopmann, M Palmblad, ... Journal of proteome research 17 (5), 1879-1886, 2018	4	2018
Response to “Comparison and Evaluation of Clustering Algorithms for Tandem Mass Spectra” J Griss, Y Perez-Riverol, M The, L Käll, JA Vizcaíno Journal of proteome research 17 (5), 1993-1996, 2018	3	2018
Focus on the spectra that matter by clustering of quantification data in shotgun proteomics M The, L Käll BioRxiv, 488015, 2019	2	2019
Uncertainty estimation of predictions of peptides’ chromatographic retention times in shotgun proteomics H Maboudi Afkham, X Qiu, M The, L Käll Bioinformatics 33 (4), 508-513, 2016	2	2016
ABRF Proteome Informatics Research Group (iPRG) 2016 Study: Inferring Proteoforms from Bottom-up Proteomics Data JY Lee, H Choi, CM Colangelo, D Davis, MR Hoopmann, L Käll, H Lam, ... Journal of biomolecular techniques: JBT 29 (2), 39, 2018	1	2018
Speeding Up Percolator JT Halloran, H Zhang, K Kara, C Renggli, M The, C Zhang, DM Rocke, ... Journal of proteome research 18 (9), 3353-3359, 2019		2019
Integrated identification and quantification error probabilities for shotgun proteomics M The, L Käll Molecular & Cellular Proteomics 18 (3), 561-570, 2019		2019
Statistical and machine learning methods to analyze large-scale mass spectrometry data M The KTH Royal Institute of Technology, Stockholm, Sweden., 2018		2018

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