Center for Education in Proteomic Analysis
Summer Proteomics Workshop 2018
The next Summer Proteomics Workshop is July 11-13, 2018. Gain hands-on training and experience in Proteomics Analysis. The workshop is designed for entry-level to senior researchers familiar with biology, molecular biology, and biochemistry but without working knowledge of proteomics.
Deadline to register: June 29. Summer Proteomics Workshop 2018 Registration [PDF]
- Introductory Proteomics
- Sample Preparation
- Mass Spectrometry
- Data Acquisition and Interpretation
- Advanced Applications (molecular weight and protein identification; protein-protein interactions; post-translational modifications; quantitative proteomics)
The Center for Education in Proteomic Analysis (CEPA) provides state-of-the-art technology for characterization of protein/peptide identity, differential proteome profiling, post-translational modification (PTM), structure, interactions, and quantification. CEPA is available to CSULB community, as well as other CSU campuses and external users worldwide, and it operates as a fee-for-service resource. The Center also serves as a resource for training, education, and consultation for Proteomics applications and will work with you from initial experimental design through publication and/or proposal.
The CEPA Proteomics Core Facility is equipped with 1D and 2D gel electrophoresis units, ultra-high resolution image scanners, Progenesis 2D gel analysis software, thermomixers, nano-flow 2D liquid chromatography, biological and chemical hoods, and speedvac for mass spectrometry sample preparation. The Center also features two state-of-the-art systems: an ABSciex 4800 MALDI-TOF/TOF and a Thermo Surveyor-ESI-LTQ Ion Trap. CEPA can perform quantitative proteomics experiments using labeled (SILAC or iTRAQ) or label-free approaches. Comprehensive data analysis is provided through a variety of database search engines, Mascot and software packages including GPS Explorer, Protein Pilot, and Thermo Proteomics Software. CEPA can also aid in bioinformatics analysis using DAVID and STRING.