eagle-i University of Texas at San AntonioUniversity of Texas at San Antonio
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RCMI Proteomics & Protein Biomarkers Core

Director: Haskins, William E., Ph.D.


The RCMI Proteomics & Protein Biomarkers Cores at the University of Texas at San Antonio (UTSA) are focused on capillary liquid chromatography-mass spectrometry (LC/MS) and -tandem mass spectrometry (LC/MS/MS), to identify, characterize, and quantify proteins. The Proteomics Core develops novel methods, while the Protein Biomarkers Core applies these methods to discover and validate novel protein biomarkers of disease. Highly specific and sensitive protein biomarkers offer profound health care benefits for diagnosis and treatment, including understanding and reducing health disparities in minority populations. Moreover, protein biomarkers are promising therapeutic targets for new drugs.The RCMI Program at UTSA is funded by Research Centers in Minority Institutions (RCMI) grants from the National Center for Research Resources (5 G12RR013646-12) and the National Insitute on Minority Health & Health Disparities (NIMHD)(8 G12MD007591-12) from the National Institutes of Health (NIH), UTSA, and generous donations.






  • Matrix Science Mascot Search access ( Access service )

    Includes searchable access to the following reference data: peptide mass fingerprint, sequence query, and MS/MS ion searches.


  • Ingenuity Pathway Analysis ( Software )

  • MaxQuant software ( Software )

    "MaxQuant is a quantitative proteomics software package designed for analyzing large mass-spectrometric data sets. It is specifically aimed at high-resolution MS data. Several labeling techniques as well as label-free quantification are supported. MaxQuant is freely available and can be downloaded from this site. The download includes the search engine Andromeda which is integrated into MaxQuant as well as the Viewer application for inspection of raw data and identification and quantification results."

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Last updated: 2014-10-27T15:59:56.253-05:00

Copyright © 2016 by the President and Fellows of Harvard College
The eagle-i Consortium is supported by NIH Grant #5U24RR029825-02 / Copyright 2016