Alexey Nesvizhskii

Summary

Affiliation: University of Michigan
Country: USA

Publications

  1. pmc A statistical model-building perspective to identification of MS/MS spectra with PeptideProphet
    Kelvin Ma
    Department of Statistics, Purdue University, 250 N University Street, West Lafayette, Indiana, USA
    BMC Bioinformatics 13:S1. 2012
  2. pmc Computational and informatics strategies for identification of specific protein interaction partners in affinity purification mass spectrometry experiments
    Alexey I Nesvizhskii
    Department of Pathology, University of Michigan, Ann Arbor, MI 48109, USA
    Proteomics 12:1639-55. 2012
  3. pmc Examination of the relationship between essential genes in PPI network and hub proteins in reverse nearest neighbor topology
    Kang Ning
    Department of Pathology, University of Michigan, Ann Arbor, MI 48109, USA
    BMC Bioinformatics 11:505. 2010
  4. pmc The utility of mass spectrometry-based proteomic data for validation of novel alternative splice forms reconstructed from RNA-Seq data: a preliminary assessment
    Kang Ning
    Department of Pathology, University of Michigan, Ann Arbor, MI 48109, USA
    BMC Bioinformatics 11:S14. 2010
  5. pmc A survey of computational methods and error rate estimation procedures for peptide and protein identification in shotgun proteomics
    Alexey I Nesvizhskii
    Department of Pathology, University of Michigan, Ann Arbor, MI 48109, USA
    J Proteomics 73:2092-123. 2010
  6. ncbi request reprint Dynamic spectrum quality assessment and iterative computational analysis of shotgun proteomic data: toward more efficient identification of post-translational modifications, sequence polymorphisms, and novel peptides
    Alexey I Nesvizhskii
    Institute for Systems Biology, Seattle, Washington 98103, USA
    Mol Cell Proteomics 5:652-70. 2006
  7. ncbi request reprint False discovery rates and related statistical concepts in mass spectrometry-based proteomics
    Hyungwon Choi
    Department of Pathology, University of Michigan, Ann Arbor, Michigan 48109, USA
    J Proteome Res 7:47-50. 2008
  8. ncbi request reprint Statistical validation of peptide identifications in large-scale proteomics using the target-decoy database search strategy and flexible mixture modeling
    Hyungwon Choi
    Department of Pathology and Biostatistics, University of Michigan, Ann Arbor, Michigan, USA
    J Proteome Res 7:286-92. 2008
  9. ncbi request reprint Semisupervised model-based validation of peptide identifications in mass spectrometry-based proteomics
    Hyungwon Choi
    Department of Pathology and Biostatistics, University of Michigan, Ann Arbor, Michigan 48109, USA
    J Proteome Res 7:254-65. 2008
  10. pmc Adaptive discriminant function analysis and reranking of MS/MS database search results for improved peptide identification in shotgun proteomics
    Ying 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

Research Grants

Collaborators

Detail Information

Publications34

  1. pmc A statistical model-building perspective to identification of MS/MS spectra with PeptideProphet
    Kelvin 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...
  2. pmc Computational and informatics strategies for identification of specific protein interaction partners in affinity purification mass spectrometry experiments
    Alexey 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...
  3. pmc Examination of the relationship between essential genes in PPI network and hub proteins in reverse nearest neighbor topology
    Kang 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)...
  4. pmc The utility of mass spectrometry-based proteomic data for validation of novel alternative splice forms reconstructed from RNA-Seq data: a preliminary assessment
    Kang 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...
  5. pmc A survey of computational methods and error rate estimation procedures for peptide and protein identification in shotgun proteomics
    Alexey 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...
  6. ncbi request reprint Dynamic spectrum quality assessment and iterative computational analysis of shotgun proteomic data: toward more efficient identification of post-translational modifications, sequence polymorphisms, and novel peptides
    Alexey I Nesvizhskii
    Institute for Systems Biology, Seattle, Washington 98103, USA
    Mol Cell Proteomics 5:652-70. 2006
    ....
  7. ncbi request reprint False discovery rates and related statistical concepts in mass spectrometry-based proteomics
    Hyungwon 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...
  8. ncbi request reprint Statistical validation of peptide identifications in large-scale proteomics using the target-decoy database search strategy and flexible mixture modeling
    Hyungwon 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...
  9. ncbi request reprint Semisupervised model-based validation of peptide identifications in mass spectrometry-based proteomics
    Hyungwon Choi
    Department of Pathology and Biostatistics, University of Michigan, Ann Arbor, Michigan 48109, USA
    J Proteome Res 7:254-65. 2008
    ....
  10. pmc Adaptive discriminant function analysis and reranking of MS/MS database search results for improved peptide identification in shotgun proteomics
    Ying 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...
  11. pmc Improved sequence tag generation method for peptide identification in tandem mass spectrometry
    Xia 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...
  12. pmc Computational analysis of unassigned high-quality MS/MS spectra in proteomic data sets
    Kang 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...
  13. pmc Significance analysis of spectral count data in label-free shotgun proteomics
    Hyungwon 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...
  14. pmc Proteomic interrogation of androgen action in prostate cancer cells reveals roles of aminoacyl tRNA synthetases
    Adaikkalam 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...
  15. pmc Quantitative proteomic profiling of prostate cancer reveals a role for miR-128 in prostate cancer
    Amjad 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...
  16. pmc "Topological significance" analysis of gene expression and proteomic profiles from prostate cancer cells reveals key mechanisms of androgen response
    Adaikkalam Vellaichamy
    Departments of Pathology, Internal Medicine, Human Genetics, School of Medicine, University of Michigan, Ann Arbor, Michigan, USA
    PLoS ONE 5:e10936. 2010
    ....
  17. ncbi request reprint Analysis and validation of proteomic data generated by tandem mass spectrometry
    Alexey 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...
  18. ncbi request reprint Investigating MS2/MS3 matching statistics: a model for coupling consecutive stage mass spectrometry data for increased peptide identification confidence
    Peter 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...
  19. ncbi request reprint Protein identification by tandem mass spectrometry and sequence database searching
    Alexey I Nesvizhskii
    Department of Pathology, University of Michigan, Ann Arbor, USA
    Methods Mol Biol 367:87-119. 2007
    ....
  20. ncbi request reprint Empirical statistical model to estimate the accuracy of peptide identifications made by MS/MS and database search
    Andrew 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...
  21. ncbi request reprint 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 t
    Priska 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...
  22. ncbi request reprint 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 s
    Priska 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...
  23. ncbi request reprint A statistical model for identifying proteins by tandem mass spectrometry
    Alexey 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...
  24. ncbi request reprint Analysis, statistical validation and dissemination of large-scale proteomics datasets generated by tandem MS
    Alexey 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...
  25. pmc Integration with the human genome of peptide sequences obtained by high-throughput mass spectrometry
    Frank 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...
  26. ncbi request reprint Interpretation of shotgun proteomic data: the protein inference problem
    Alexey I Nesvizhskii
    Institute for Systems Biology, Seattle, Washington 98103, USA
    Mol Cell Proteomics 4:1419-40. 2005
    ....
  27. ncbi request reprint Do we want our data raw? Including binary mass spectrometry data in public proteomics data repositories
    Lennart 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...
  28. ncbi request reprint Human Plasma PeptideAtlas
    Eric 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...
  29. pmc Investigation of neutral loss during collision-induced dissociation of peptide ions
    Daniel 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...
  30. pmc The PeptideAtlas project
    Frank 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...
  31. doi request reprint Improving sensitivity by probabilistically combining results from multiple MS/MS search methodologies
    Brian 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...
  32. ncbi request reprint Optimized peptide separation and identification for mass spectrometry based proteomics via free-flow electrophoresis
    Johan 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
    ....
  33. pmc Analysis of the Saccharomyces cerevisiae proteome with PeptideAtlas
    Nichole 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...
  34. ncbi request reprint Experimental protein mixture for validating tandem mass spectral analysis
    Andrew 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 Grants5

  1. Analysis and Statistical Validation of Proteomic Datasets
    Alexey Nesvizhskii; Fiscal Year: 2007
    ....
  2. Analysis and Statistical Validation of Proteomic Datasets
    Alexey Nesvizhskii; Fiscal Year: 2009
    ....
  3. Computational tools for mass spectrometry-based interactome data
    Alexey I Nesvizhskii; Fiscal Year: 2010
    ..All computational tools developed as a part of this proposal will be made freely available to the research community. ..