Proteomics & Integrative Bioinformatics Lab
Our research interests are in the fields of proteomics and integrative bioinformatics. On the bioinformatics side,
we are focusing on the development of computational methods and tools for processing and extracting biological information from complex biological
datasets. This includes computational and statistical methods for mass spectrometry-based proteomics, interactome analysis using affinity
purification mass spectrometry (AP-MS) technology, proteogenomics, metabolomics, global analysis of RNA-Seq transcriptome and proteome profiles,
and multi-omics data integration (RNA-Seq, proteomics, genomics, etc.) for reconstruction of pathways deregulated in cancer. Our lab has
developed and maintains many computational resources widely used by the proteomics community worldwide, described on our Software page.
In 2015 our lab has expanded to include the Proteomics Resource Facility (PRF) at the University of Michigan. Directed by Dr. Nesvizhskii, PRF
aims to provide state-of-the-art instrumentation, technical expertise and bioinformatics support to the University of Michigan research
community. We are actively collaborating with many biologists and translational scientists, at the University of Michigan and internationally,
on a wide range of projects that involve proteomics technology. Taking advantage of our strengths in bioinformatics, we are also developing new
and improved proteomics methods such as Data Independent Acquisition (DIA) mass spectrometry for improved label-free protein quantification.
Bioinformatics tools and resources we developed: SOFTWARE
Proteomics Resource Facility: PRF
Current and former lab members: MEMBERS
News in the lab or about the lab: NEWS
Selected Recent NewsFor more news see: NEWS
April 2017: "MSFragger: ultrafast and comprehensive peptide identification in mass spectrometry-based proteomics" has been published in Nature Methods. You can find links to this and all other computational tools on our SOFTWARE page.
April 2017: Applications are invited from faculty with appointment in the University of Michigan Medical School for proteomics related Pilot Projects that intend to use the state-of-the-art Proteomics Resource Facility (PRF) at the University of Michigan Medical School that is led by Dr. Alexey Nesvizhskii. More information and how to apply is here.
April 2017: Announcing BioContainers - an open-source and community-driven framework which provides platform independent executable environments for bioinformatics software using Docker containers. The project was initiated by Felipe Leprevost, and the manuscript describing this effort has been published in Bioinformatics. Read the manuscript here.
March 2017: Alexey Nesvizhskii received Gilbert S. Omenn Computational Proteomics Award. This award recognizes the specific achievements of scientists that have developed bioinformatics, computational, statistical methods and/or software used by the proteomics community. The award was presented at the 2017 US HUPO annual conference in San Diego, CA.Sept 2016: Post-doctoral positions available in the lab
Sept 2016: Brendan Veeneman successfully defended his Ph.D. thesis "Development and Application of Methods to Discover Cancer-Associated Transcript Variants"
June 2016: New mass spectrometer, Q Exactive HF, is installed in the Proteomics Resource Facility and now fully operational
June 2016: BatMass software is published: "BatMass: a Java Software Platform for LC-MS Data Visualization in Proteomics and Metabolomics", Journal of Proteome Research
June 2016: DIA-Umpire version 2 for data independent acquisition (DIA) mass spectrometry is released. The manuscript "Untargeted, spectral library-free analysis of data-independent acquisition proteomics data generated using Orbitrap mass spectrometers" is published in Proteomics. News coverage: article in GenomeWeb (July 2016)
Apr 2016: New version of ProHits laboratory information management system (LIMS) is released (A.C. Gingras lab), describing incorporation of our new tools for data independent acquisition analysis (DIA-Umpire, mapDIA). The manuscript "Data Independent Acquisition analysis in ProHits 4.0" is published in J Proteomics
March 2016: Proteomics Resource Facility announces Pilot Project Program for the Department of Pathology Investigators
March 2016 Our lab contributed bioinformatics analysis to manuscript from Yali Dou lab published in Cell Stem Cell, "MLL1 Inhibition Reprograms Epiblast Stem Cells to Naive Pluripotency". News coverage: article in Science Daily
Jan 2016: New method for RNA-Seq analysis of alternative splicing developed by Brendan Veeneman is descibed in the manuscript "Two-pass alignment improves novel splice junction quantification" published in Bioinformatics
Jan 2016: New post-doctoral fellow Guo Ci Teo joins the lab from the University of Singapore, where he received his Ph.D. in Biostatistics working in Hyungwon Choi's lab
Jan 2016: Chih-Chiang Tsou successfully defended his Ph.D. thesis "Computational Framework for Data-Independent Acquisition Proteomics". Chih-Chiang is now a Senior Bioinformatics Scientist at Immatics (Houston, Texas)
Nov 2015: QPROT software for statistical analysis of intensity-based label-free quantification data is released. The manuscript "QPROT: Statistical method for testing differential expression using protein-level intensity data in label-free quantitative proteomics" is published in Proteomics
Nov 2015: mapDIA software for statistical modeling of quantification data from data independent acquisition (DIA)mass spectrometry experiments is released. The manuscript "mapDIA: Preprocessing and statistical analysis of quantitative proteomics data from data independent acquisition mass spectrometry" is published in Proteomics
Sept 2015: Avinash Shanmugam successfully defended his Ph.D. thesis "Integrative analysis frameworks for improved peptide and protein identifications from tandem mass spectrometry data". Avinash is now a Bioinformatics Scientist at Recombine (New York)
Aug 2015: Manuscript on high-throughput RNA sequencing and bioinformatics modeling to comprehensively characterize the landscape of antisense expression in cancer is published in Genome Research, "The landscape of antisense gene expression in human cancers". The OncoNAT repository provides source code for analysing of strand-specific RNA Sequencing (ssRNASeq). Congratulation to Alejandro Balbin, the lead author of this studyFor more news see: NEWS
- DIA-Umpire tool for data independent acquisition proteomics data in Nature Methods
- Comprehensive review on Proteogenomics in Nature Methods
- Utility of RNA-seq and GPMDB for improving protein identification in J Prot Research
- SAINTexpress software for AP-MS data in J Proteomics
- On reconstruction of cancer pathways using omics data integration in Nature Commun.
- CRAPome is published in Nature Methods
- iProphet method and software is published in Molecular & Cellular Proteomics
- Special issue of the journal Proteomics on Protein Complexes and Interaction Networks
- New manuscripts on joint analysis of proteomic and RNA-seq transcriptomic data
- SAINT-MS1 for intensity-based AP-MS published in J Prot Research
- SAINT 2.0 method for AP-MS data published in Nature Methods
- Abacus: software for label-free proteomics now available
- Comprehensive review on peptide/protein error rates in J. Proteomics
- Comprehensive review on scoring protein interactions in AP-MS data in Proteomics
- Global yeast protein kinase and phosphatase interaction network published in Science
- PeptideProphet and ProteinProphet manuscripts reach 2000 citations
- Proteome Informatics of Cancer Training Program at U Michigan
- Watch us talk about our research on YouTube