Empirical statistical model to estimate the accuracy of peptide identifications made by MS/MS and database search A Keller, AI Nesvizhskii, E Kolker, R Aebersold Analytical chemistry 74 (20), 5383-5392, 2002 | 5600 | 2002 |
A statistical model for identifying proteins by tandem mass spectrometry AI Nesvizhskii, A Keller, E Kolker, R Aebersold Analytical chemistry 75 (17), 4646-4658, 2003 | 5274 | 2003 |
The CRAPome: a contaminant repository for affinity purification–mass spectrometry data D Mellacheruvu, Z Wright, AL Couzens, JP Lambert, NA St-Denis, T Li, ... Nature methods 10 (8), 730–736, 2013 | 1704 | 2013 |
MSFragger: ultrafast and comprehensive peptide identification in mass spectrometry–based proteomics AT Kong, FV Leprevost, DM Avtonomov, D Mellacheruvu, AI Nesvizhskii Nature methods 14 (5), 513-520, 2017 | 1279 | 2017 |
The landscape of circular RNA in cancer JN Vo, M Cieslik, Y Zhang, S Shukla, L Xiao, Y Zhang, YM Wu, ... Cell 176 (4), 869-881. e13, 2019 | 1263 | 2019 |
Interpretation of shotgun proteomic data: the protein inference problem AI Nesvizhskii, R Aebersold Molecular & cellular proteomics 4 (10), 1419-1440, 2005 | 1215 | 2005 |
The peptideatlas project F Desiere, EW Deutsch, NL King, AI Nesvizhskii, P Mallick, J Eng, S Chen, ... Nucleic acids research 34 (suppl_1), D655-D658, 2006 | 927 | 2006 |
A guided tour of the Trans‐Proteomic Pipeline EW Deutsch, L Mendoza, D Shteynberg, T Farrah, H Lam, N Tasman, ... Proteomics 10 (6), 1150-1159, 2010 | 849 | 2010 |
Analysis and validation of proteomic data generated by tandem mass spectrometry AI Nesvizhskii, O Vitek, R Aebersold Nature methods 4 (10), 787-797, 2007 | 827 | 2007 |
SAINT: probabilistic scoring of affinity purification–mass spectrometry data H Choi, B Larsen, ZY Lin, A Breitkreutz, D Mellacheruvu, D Fermin, ZS Qin, ... Nature methods 8 (1), 70-73, 2011 | 808 | 2011 |
A global protein kinase and phosphatase interaction network in yeast A Breitkreutz, H Choi, JR Sharom, L Boucher, V Neduva, B Larsen, ZY Lin, ... Science 328 (5981), 1043, 2010 | 779 | 2010 |
Proteogenomics: concepts, applications and computational strategies AI Nesvizhskii Nature methods 11 (11), 1114-1125, 2014 | 774 | 2014 |
An embryonic stem cell chromatin remodeling complex, esBAF, is essential for embryonic stem cell self-renewal and pluripotency L Ho, JL Ronan, J Wu, BT Staahl, L Chen, A Kuo, J Lessard, ... Proceedings of the National Academy of Sciences 106 (13), 5181-5186, 2009 | 658 | 2009 |
DIA-Umpire: comprehensive computational framework for data-independent acquisition proteomics CC Tsou, D Avtonomov, B Larsen, M Tucholska, H Choi, AC Gingras, ... Nature methods 12 (3), 258-264, 2015 | 653 | 2015 |
A survey of computational methods and error rate estimation procedures for peptide and protein identification in shotgun proteomics AI Nesvizhskii Journal of proteomics 73 (11), 2092-2123, 2010 | 635 | 2010 |
iProphet: multi-level integrative analysis of shotgun proteomic data improves peptide and protein identification rates and error estimates D Shteynberg, EW Deutsch, H Lam, JK Eng, Z Sun, N Tasman, ... Molecular & cellular proteomics 10 (12), 2011 | 598 | 2011 |
SAINTexpress: improvements and additional features in Significance Analysis of INTeractome software G Teo, G Liu, J Zhang, AI Nesvizhskii, AC Gingras, H Choi Journal of proteomics 100, 37-43, 2014 | 595 | 2014 |
The need for guidelines in publication of peptide and protein identification data: Working Group on Publication Guidelines for Peptide and Protein Identification Data S Carr, R Aebersold, M Baldwin, AL Burlingame, K Clauser, A Nesvizhskii Molecular & Cellular Proteomics 3 (6), 531-533, 2004 | 577 | 2004 |
Proteogenomic characterization reveals therapeutic vulnerabilities in lung adenocarcinoma MA Gillette, S Satpathy, S Cao, SM Dhanasekaran, SV Vasaikar, K Krug, ... Cell 182 (1), 200-225. e35, 2020 | 479 | 2020 |
Integrated proteogenomic characterization of clear cell renal cell carcinoma DJ Clark, SM Dhanasekaran, F Petralia, J Pan, X Song, Y Hu, ... Cell 179 (4), 964-983. e31, 2019 | 467 | 2019 |