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The problem of inferring proteins from complex peptide cocktails (digestionproducts of biological samples) in shotgun proteomic workflow sets extremedemands on computational resources in respect of the required very highprocessing throughputs, rapid processing rates and reliability of results. Thisis exacerbated by the fact that, in general, a given protein cannot be definedby a fixed sequence of amino acids due to the existence of splice variants andisoforms of that protein. Therefore, the problem of protein inference could beconsidered as one of identifying sequences of amino acids with some limitedtolerance. In the current paper a model-based hardware acceleration of astructured and practical inference approach is developed and validated on amass spectrometry experiment of realistic size. We have achieved 10 timesmaximum speed-up in the co-designed workflow compared to a similarsoftware-only workflow run on the processor used for co-design.

A Structured Hardware Software Architecture for Peptide Based Diagnosis of Baylisascaris Procyonis Infection (ICIAfS14)