Title: "Label-free quantitative proteomics: methods and applications"
Speaker:Alexey I. Nesvizhskii, Deptartment of Pathology, Center for Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI
Place: HORT 117; October 25, 2011, Tuesday, 4:30pm


Mass spectrometry-based analysis of proteins and proteomes has become increasingly more quantitative. Current proteomics workflows are also very diverse in terms of experimental approaches, methods of extracting quantitative information, and how the quantitative information is utilized in the experiment. This presentation will start with a brief overview of quantitative proteomics, with a focus on accurate statistical modeling of quantitative data and on understanding advantages and limitations of different approaches. We will then present our recent studies that involve label-free protein quantitation, with more in-depth discussion in the following two contexts: 1) statistical methods for detecting differential protein expression; 2) computational methods for scoring protein-protein interactions and reconstruction of protein complexes.

Associated Reading:
1. H. Choi, D. Fermin, and A.I. Nesvizhskii. 2008. Significance analysis of spectral count data in label-free shotgun proteomics. Mol. Cell. Proteomics 7, 2373-2385.
2. H. Choi, B. Larsen, Z.Y. Lin, B. Breitkreutz, Z.S. Qin, M. Tyers, A.C. Gingras, A. I. Nesvizhskii. 2011. SAINT: probabilistic scoring of affinity purification-mass spectrometry data. Nature Methods 8: 70-73.

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