Application of machine learning method in genomics and proteomics

机器学习方法在基因组学和蛋白质组学中的应用

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Abstract

The Yale Protein Expression Database (YPED) (Shifman et. al. 2007) was developed as open source web-accessible software system for discovery and protein profiling data management. We have since expanded the software by adding a suite of tools for new protein profiling technologies, post-translational modifications, targeted proteomics, and data dissemination. The first set of tools enables us to integrate SILAC and label-free quantitation data into YPED. The second set of tools aid in the identification and site-localization of phosphopeptides. The third set were developed as a complete targeted proteomics workflow which utilizes a custom peptide spectral library database to facilitate peptide and MRM transition selection for global targeted proteomic analysis, tools for MRM method export, and an interface for collation of quantitation data results and review. Our final efforts have added a public data repository to YPED which enables the release of curated proteomic datasets for public download as either open source raw data files or Excel spreadsheets.

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