Alexey NesvizhskiiSummaryAffiliation: University of Michigan Country: USA Publications
Research Grants
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Detail Information
Publications
A statistical model-building perspective to identification of MS/MS spectra with PeptideProphetKelvin Ma
Department of Statistics, Purdue University, 250 N University Street, West Lafayette, Indiana, USA
BMC Bioinformatics 13:S1. 2012..We illustrate the use of PeptideProphet in association with the Trans-Proteomic Pipeline, a free suite of software used for protein identification...
Computational and informatics strategies for identification of specific protein interaction partners in affinity purification mass spectrometry experimentsAlexey I Nesvizhskii
Department of Pathology, University of Michigan, Ann Arbor, MI 48109, USA
Proteomics 12:1639-55. 2012..Finally, we discuss the possibility of more extended modeling of experimental AP/MS data, including integration with external information such as protein interaction predictions based on functional genomics data...- Examination of the relationship between essential genes in PPI network and hub proteins in reverse nearest neighbor topologyKang Ning
Department of Pathology, University of Michigan, Ann Arbor, MI 48109, USA
BMC Bioinformatics 11:505. 2010..In this work, we have attempted to examine the placement of essential proteins and the network topology from a different perspective by determining the correlation of protein essentiality and reverse nearest neighbor topology (RNN)... - The utility of mass spectrometry-based proteomic data for validation of novel alternative splice forms reconstructed from RNA-Seq data: a preliminary assessmentKang Ning
Department of Pathology, University of Michigan, Ann Arbor, MI 48109, USA
BMC Bioinformatics 11:S14. 2010..e. RNA-Seq) has become possible. MS-based proteomics can potentially be used as an aid for protein-level validation of novel AS events observed in RNA-Seq data... - A survey of computational methods and error rate estimation procedures for peptide and protein identification in shotgun proteomicsAlexey I Nesvizhskii
Department of Pathology, University of Michigan, Ann Arbor, MI 48109, USA
J Proteomics 73:2092-123. 2010..Commonly used methods for computing protein-level confidence scores are discussed in detail. The review concludes with a discussion of several outstanding computational issues... 
Dynamic spectrum quality assessment and iterative computational analysis of shotgun proteomic data: toward more efficient identification of post-translational modifications, sequence polymorphisms, and novel peptidesAlexey I Nesvizhskii
Institute for Systems Biology, Seattle, Washington 98103, USA
Mol Cell Proteomics 5:652-70. 2006....- False discovery rates and related statistical concepts in mass spectrometry-based proteomicsHyungwon Choi
Department of Pathology, University of Michigan, Ann Arbor, Michigan 48109, USA
J Proteome Res 7:47-50. 2008..In this work, we provide a background on statistical significance analysis in the field of mass spectrometry-based proteomics, and present our perspective on the current and future developments in this area... - Statistical validation of peptide identifications in large-scale proteomics using the target-decoy database search strategy and flexible mixture modelingHyungwon Choi
Department of Pathology and Biostatistics, University of Michigan, Ann Arbor, Michigan, USA
J Proteome Res 7:286-92. 2008..The statistical approaches presented here require that the data set contain a sufficient number of decoy (known to be incorrect) peptide identifications, which can be obtained using the target-decoy database search strategy... - Semisupervised model-based validation of peptide identifications in mass spectrometry-based proteomicsHyungwon Choi
Department of Pathology and Biostatistics, University of Michigan, Ann Arbor, Michigan 48109, USA
J Proteome Res 7:254-65. 2008.... - Adaptive discriminant function analysis and reranking of MS/MS database search results for improved peptide identification in shotgun proteomicsYing Ding
Department of Pathology, Department of Biostatistics, and Center for Computational Biology and Medicine, University of Michigan, Ann Arbor, Michigan 48109, USA
J Proteome Res 7:4878-89. 2008..A special emphasis is placed on the analysis of data generated on high mass accuracy instruments... - Improved sequence tag generation method for peptide identification in tandem mass spectrometryXia Cao
Department of Pathology, University of Michigan, Ann Arbor, Michigan 48109, USA
J Proteome Res 7:4422-34. 2008..The overall superior performance of the sequence tag-based peptide identification method is demonstrated by comparison with a commonly used SEQUEST/PeptideProphet approach... - Computational analysis of unassigned high-quality MS/MS spectra in proteomic data setsKang Ning
Department of Pathology, University of Michigan, Ann Arbor, MI, USA
Proteomics 10:2712-8. 2010..The method is applied to a large publicly available shotgun proteomic data set... - Significance analysis of spectral count data in label-free shotgun proteomicsHyungwon Choi
Department of Pathology, University of Michigan, Ann Arbor, Michigan 48109, USA
Mol Cell Proteomics 7:2373-85. 2008..We illustrate the flexibility of the model by analyzing a data set with a complicated experimental design involving cellular localization and time course... - Proteomic interrogation of androgen action in prostate cancer cells reveals roles of aminoacyl tRNA synthetasesAdaikkalam Vellaichamy
Michigan Center for Translational Pathology, University of Michigan, Ann Arbor, Michigan, USA
PLoS ONE 4:e7075. 2009..Thus, data derived from multiple proteomics platforms and transcript data coupled with informatics analysis provides a deeper insight into the functional consequences of androgen action in prostate cancer... - Quantitative proteomic profiling of prostate cancer reveals a role for miR-128 in prostate cancerAmjad P Khan
The Michigan Center for Translational Pathology, Universityof Michigan Medical School, Ann Arbor, Michigan 48109, USA
Mol Cell Proteomics 9:298-312. 2010..Taken together, our profiles of the proteomic alterations of prostate cancer progression revealed miR-128 as a potentially important negative regulator of prostate cancer cell invasion... - "Topological significance" analysis of gene expression and proteomic profiles from prostate cancer cells reveals key mechanisms of androgen responseAdaikkalam Vellaichamy
Departments of Pathology, Internal Medicine, Human Genetics, School of Medicine, University of Michigan, Ann Arbor, Michigan, USA
PLoS ONE 5:e10936. 2010.... - Analysis and validation of proteomic data generated by tandem mass spectrometryAlexey I Nesvizhskii
University of Michigan, Department of Pathology and Center for Computational Medicine and Biology, Ann Arbor, Michigan 48105, USA
Nat Methods 4:787-97. 2007..We place special emphasis on the elaboration of results that are supported by sound statistical arguments... - Investigating MS2/MS3 matching statistics: a model for coupling consecutive stage mass spectrometry data for increased peptide identification confidencePeter J Ulintz
Department of Biological Chemistry, University of Michigan, Ann Arbor, Michigan 48103, USA
Mol Cell Proteomics 7:71-87. 2008..This work also addresses the overall value of generating MS(3) data as compared with an MS(2)-only approach with a focus on the analysis of phosphopeptide data... - Protein identification by tandem mass spectrometry and sequence database searchingAlexey I Nesvizhskii
Department of Pathology, University of Michigan, Ann Arbor, USA
Methods Mol Biol 367:87-119. 2007.... - Empirical statistical model to estimate the accuracy of peptide identifications made by MS/MS and database searchAndrew Keller
Institute for Systems Biology, Seattle, Washington 98103, USA
Anal Chem 74:5383-92. 2002..This analysis makes it possible to filter large volumes of MS/MS database search results with predictable false identification error rates and can serve as a common standard by which the results of different research groups are compared... - The application of new software tools to quantitative protein profiling via isotope-coded affinity tag (ICAT) and tandem mass spectrometry: I. Statistically annotated datasets for peptide sequences and proteins identified via the application of ICAT and tPriska D von Haller
Institute for Systems Biology, 1441 North 34th Street, Seattle, WA 98103, USA
Mol Cell Proteomics 2:426-7. 2003..In total, these data sets contained 7667 individual peptide identifications, which represented 2669 unique peptide sequences, corresponding to 685 proteins and related protein groups... - The application of new software tools to quantitative protein profiling via isotope-coded affinity tag (ICAT) and tandem mass spectrometry: II. Evaluation of tandem mass spectrometry methodologies for large-scale protein analysis, and the application of sPriska D von Haller
Institute for Systems Biology, 1441 North 34th Street, Seattle, WA 98103, USA
Mol Cell Proteomics 2:428-42. 2003..Finally, by repeating the experiment, information relating to the general reproducibility and validity of this approach to large-scale proteomic analyses was also obtained... - A statistical model for identifying proteins by tandem mass spectrometryAlexey I Nesvizhskii
Institute for Systems Biology, 1441 North 34th Street, Seattle, Washington 98103, USA
Anal Chem 75:4646-58. 2003..Fast, consistent, and transparent, it provides a standard for publishing large-scale protein identification data sets in the literature and for comparing the results obtained from different experiments... - Analysis, statistical validation and dissemination of large-scale proteomics datasets generated by tandem MSAlexey I Nesvizhskii
Institute for Systems Biology, 1441 N 34th Street, Seattle, WA 98103, USA
Drug Discov Today 9:173-81. 2004..Here, we review currently available computational tools and discuss the need for statistical criteria in the analysis of large proteomics datasets... - Integration with the human genome of peptide sequences obtained by high-throughput mass spectrometryFrank Desiere
Nestle Research Center, 1000 Lausanne 26, Switzerland
Genome Biol 6:R9. 2005..This resource could serve as an expandable repository for MS-derived proteome information... - Interpretation of shotgun proteomic data: the protein inference problemAlexey I Nesvizhskii
Institute for Systems Biology, Seattle, Washington 98103, USA
Mol Cell Proteomics 4:1419-40. 2005.... - Do we want our data raw? Including binary mass spectrometry data in public proteomics data repositoriesLennart Martens
Department of Biochemistry, Faculty of Medicine and Health Sciences, Ghent University, Ghent, Belgium
Proteomics 5:3501-5. 2005..Finally, some suggestions are made for both immediate and future storage of MS data in public repositories... - Human Plasma PeptideAtlasEric W Deutsch
Institute for Systems Biology, Seattle, WA 98103, USA
Proteomics 5:3497-500. 2005..The resulting compendium of peptides and their associated samples, proteins, and genes is made publicly available as a reference for future research on human plasma... - Investigation of neutral loss during collision-induced dissociation of peptide ionsDaniel B Martin
Institute for Systems Biology, Seattle, Washington 98103, USA
Anal Chem 77:4870-82. 2005..Clarification of the rules that govern neutral loss, when incorporated into analysis software, will improve our ability to correctly assign spectra to peptide sequences... - The PeptideAtlas projectFrank Desiere
Institute for Systems Biology, Seattle, WA, USA
Nucleic Acids Res 34:D655-8. 2006..Here we present a summary of our process and details about the Human, Drosophila and Yeast PeptideAtlas builds... - Improving sensitivity by probabilistically combining results from multiple MS/MS search methodologiesBrian C Searle
Proteome Software Inc, 1340 S W Bertha Boulevard, Suite 201, Portland, Oregon 97219 2039, USA
J Proteome Res 7:245-53. 2008..The increased rate of peptide assignments also translates into a substantially larger number of protein identifications in LC/MS/MS studies compared to a typical analysis using a single database-search tool... - Optimized peptide separation and identification for mass spectrometry based proteomics via free-flow electrophoresisJohan Malmstrom
Institute for Molecular Systems Molecular Biology, Swiss Federal Institute for Technology Zürich ETH, Hoenggerberg 8093 Zürich, Switzerland
J Proteome Res 5:2241-9. 2006.... - Analysis of the Saccharomyces cerevisiae proteome with PeptideAtlasNichole L King
Institute for Systems Biology, N 34th Street, Seattle, WA 98103, USA
Genome Biol 7:R106. 2006..We highlight the use of this resource for data mining, construction of high quality lists for targeted proteomics, validation of proteins, and software development... - Experimental protein mixture for validating tandem mass spectral analysisAndrew Keller
Institute for Systems Biology, Seattle, Washington 98103, USA
OMICS 6:207-12. 2002..We show how the sensitivity and error rate are affected by the use of various filtering criteria based upon SEQUEST scores and the number of tryptic termini of assigned peptides...
Research Grants
- Analysis and Statistical Validation of Proteomic DatasetsAlexey Nesvizhskii; Fiscal Year: 2007....
- Analysis and Statistical Validation of Proteomic DatasetsAlexey Nesvizhskii; Fiscal Year: 2009....
- Computational tools for mass spectrometry-based interactome dataAlexey I Nesvizhskii; Fiscal Year: 2010..All computational tools developed as a part of this proposal will be made freely available to the research community. ..