Key Documents
Joshua Elias
Academic Appointments
- Assistant Professor, Chemical and Systems Biology
- Member, Cancer Center
Contact Information
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Academic Offices
Personal Information Email
Professional Snapshot
Professional Education
| Ph.D.: | Harvard University, Cell Biology (2006) |
| B.S.: | Cornell University, Biology, Genetics (1998) |
Graduate & Fellowship Program Affiliations
Scientific Focus
Research Interests
The Elias Lab seeks to develop and apply methods for large scale proteome characterization to solve fundamental problems in cell biology and disease. The growing field of proteomics has the lofty goal of characterizing the proteins in any isolated complex, subcellular compartment, cultured cell line or tissue. We use mass spectrometry-based approaches which can do more than simply determining the identity of a protein isolated in a polyacrylamide gel -- rapidly advancing technologies are allowing us to measure dynamic changes in protein abundances, post-translational modification states, splice isoforms, interaction partners, and localization across multiple cell states. The combination of liquid chromatography with tandem mass spectrometry (LC-MS/MS) has emerged as the most robust technology for making proteome-scale discoveries. Although the tools of proteomics have greatly advanced in recent years, many challenges lie ahead. Our lab focuses on developing new methods in protein fractionation, instrumentation, and data analysis to meet these challenges, and then applies them to studying important biomedical paradigms, including cancer, aging, and stem cell biology.
Publications
- Proteomic profiling of gamma-secretase substrates and mapping of substrate requirements. PLoS Biol. 2008; (10): e257
- Target-decoy search strategy for increased confidence in large-scale protein identifications by mass spectrometry. Nat Methods. 2007; (3): 207-14
- Comparative evaluation of mass spectrometry platforms used in large-scale proteomics investigations. Nat Methods. 2005; (9): 667-75
- Intensity-based protein identification by machine learning from a library of tandem mass spectra. Nat Biotechnol. 2004; (2): 214-9
- The impact of peptide abundance and dynamic range on stable-isotope-based quantitative proteomic analyses. J Proteome Res. 2008; (11): 4756-65
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