This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. Primary support for the subproject and the subproject's principal investigator may have been provided by other sources, including other NIH sources. The Total Cost listed for the subproject likely represents the estimated amount of Center infrastructure utilized by the subproject, not direct funding provided by the NCRR grant to the subproject or subproject staff. A collaboration with professor Qiang Cheng, a bioinformatician at Southern Illinois University in Carbondale, has been initiated with the intention of developing a machine learning approach for the detection of gramzyme cleavage products. The approach will use tandem MS data from 2D gel spots to identify a list of candidate proteins and then accurate mass and time MS1 data will be mapped onto the identified sequences before a machine learning algorithm attempts to identify the cleavage products. It is expected that this approach will combat the under sampling issue associated with data dependent acquisition of tandem MS data, and thus increase the sensitivity of an already completed method.
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