Dr. Nesvizhskii is a Principal Investigator in the Proteome Bioinformatics Lab at the University of Michigan. He received a Ph.D. in Physics from the University of Washington (2001), and a M.S. in Physics and Technology from St. Petersburg State Technical University, Russia (1995).
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UniversityUniversity of Michigan
Dr. Nesvizhskii's research interest is in the field of quantitative proteomics, with a focus on the development of computational methods for processing and extracting biological information from complex proteomic datasets. Similar to other global high throughput technologies such as microarray gene expression analysis, proteomics is extremely dependent on the ability to quickly and reliably analyze large amounts of experimental data. One of the aims of Dr. Nesvizhskii's research is to close the critical gap between the development of high throughput quantitative proteomics methods and the ability to deal with the resulting data deluge and to convert it into new biological knowledge or to develop new disease biomarkers. The efforts in his lab range from the development of computational tools and statistical methods for mass spectrometry-based peptide and protein identification and quantification, to the establishment of guidelines and standards for proteomic data analysis and publication, to the creation of public databases and proteomic data repositories and integration of proteomic with genomic and other types of biological data
LuciPHOr2: Site localization of generic post-translational modifications from tandem mass spectrometry data. Fermin D, Avtonomov D, Choi H, Nesvizhskii AI. Bioinformatics. 2014 Nov 25. pii: btu788. [Epub ahead of print] PMID: 25429062 [PubMed - as supplied by publisher]
Proteogenomics: concepts, applications and computational strategies. Nesvizhskii AI. Nat Methods. 2014 Oct 30;11(11):1114-25. doi: 10.1038/nmeth.3144. PMID: 25357241 [PubMed - in process]
Utility of RNA-seq and GPMDB protein observation frequency for improving the sensitivity of protein identification by tandem MS. Shanmugam AK, Yocum AK, Nesvizhskii AI. J Proteome Res. 2014 Sep 5;13(9):4113-9. doi: 10.1021/pr500496p. Epub 2014 Jul 28. PMID: 25026199 [PubMed - in process]
Global phosphoproteomic profiling reveals distinct signatures in B-cell non-Hodgkin lymphomas. Rolland D, Basrur V, Conlon K, Wolfe T, Fermin D, Nesvizhskii AI, Lim MS, Elenitoba-Johnson KS. Am J Pathol. 2014 May;184(5):1331-42. doi: 10.1016/j.ajpath.2014.01.036. Epub 2014 Mar 22. PMID: 24667141 [PubMed - in process] Free Article
The yeast Sks1p kinase signaling network regulates pseudohyphal growth and glucose response. Johnson C, Kweon HK, Sheidy D, Shively CA, Mellacheruvu D, Nesvizhskii AI, Andrews PC, Kumar A. PLoS Genet. 2014 Mar 6;10(3):e1004183. doi: 10.1371/journal.pgen.1004183. eCollection 2014 Mar. PMID: 24603354 [PubMed - in process] Free PMC Article
SAINTexpress: improvements and additional features in Significance Analysis of INTeractome software. Teo G, Liu G, Zhang J, Nesvizhskii AI, Gingras AC, Choi H.
J Proteomics. 2014 Apr 4;100:37-43. doi: 10.1016/j.jprot.2013.10.023. Epub 2013 Oct 26. PMID: 24513533 [PubMed - in process]
Toward more transparent and reproducible omics studies through a common metadata checklist and data publications. Kolker E, Özdemir V, Martens L, Hancock W, Anderson G, Anderson N, Aynacioglu S, Baranova A, Campagna SR, Chen R, Choiniere J, Dearth SP, Feng WC, Ferguson L, Fox G, Frishman D, Grossman R, Heath A, Higdon R, Hutz MH, Janko I, Jiang L, Joshi S, Kel A, Kemnitz JW, Kohane IS, Kolker N, Lancet D, Lee E, Li W, Lisitsa A, Llerena A, Macnealy-Koch C, Marshall JC, Masuzzo P, May A, Mias G, Monroe M, Montague E, Mooney S, Nesvizhskii A, Noronha S, Omenn G, Rajasimha H, Ramamoorthy P, Sheehan J, Smarr L, Smith CV, Smith T, Snyder M, Rapole S, Srivastava S, Stanberry L, Stewart E, Toppo S, Uetz P, Verheggen K, Voy BH, Warnich L, Wilhelm SW, Yandl G. OMICS. 2014 Jan;18(1):10-4. doi: 10.1089/omi.2013.0149. PMID: 24456465 [PubMed - indexed for MEDLINE]
Hands-on workshops as an effective means of learning advanced technologies including genomics, proteomics and bioinformatics. Reisdorph N, Stearman R, Kechris K, Phang TL, Reisdorph R, Prenni J, Erle DJ, Coldren C, Schey K, Nesvizhskii A, Geraci M. Genomics Proteomics Bioinformatics. 2013 Dec;11(6):368-77. doi: 10.1016/j.gpb.2013.10.002. Epub 2013 Dec 6. PMID: 24316330 [PubMed - indexed for MEDLINE] Free PMC Article
Reconstructing targetable pathways in lung cancer by integrating diverse omics data. Balbin OA, Prensner JR, Sahu A, Yocum A, Shankar S, Malik R, Fermin D, Dhanasekaran SM, Chandler B, Thomas D, Beer DG, Cao X, Nesvizhskii AI, Chinnaiyan AM. Nat Commun. 2013;4:2617. doi: 10.1038/ncomms3617. PMID: 24135919 [PubMed - indexed for MEDLINE] Free PMC Article
Comprehensive analysis of protein digestion using six trypsins reveals the origin of trypsin as a significant source of variability in proteomics.
Walmsley SJ, Rudnick PA, Liang Y, Dong Q, Stein SE, Nesvizhskii AI.
J Proteome Res. 2013 Dec 6;12(12):5666-80. doi: 10.1021/pr400611h. Epub 2013 Nov 14.
PMID: 24116745 [PubMed - indexed for MEDLINE] Free PMC Article