Anthony S Barente

Abstract Emergence of biobank level proteomic datasets with extensive phenotype linkage has significantly improved our understanding of proteomic drivers in health and ushered in a flurry of disease risk prediction models. However, differences in cohorts and proteomic assays can significantly undermine transferability of proteomic models, severely limiting their general use.

Abstract We present a computational tool, MARLOWE, for source organism characterization of unknown, forensic biological samples. The intent of MARLOWE is to address a gap in applying proteomics data analysis to forensic applications. MARLOWE produces a list of potential source organisms given confident peptide tags derived from de novo peptide sequencing and a statistical approach to assign peptides to organisms in a probabilistic manner, based on a broad sequence database.