Infrastructure

基础设施

• 批准号: 8798314
• 负责人: Nuno Bandeira
• 金额: $ 26万
• 依托单位: UNIVERSITY OF CALIFORNIA, SAN DIEGO
• 依托单位国家: 美国
• 资助国家: 美国
• 起止时间: 至
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/8798314
• 关键词: Adoption; Algorithms; Antibiotics; Antibody Repertoire; Architecture; Archives; Biological; Biological Factors; Biological Markers; Cancer Patient; Cataract; Chemicals; Clinical; Communities; Complex; Data; Development; Drug toxicity; Environment; Fingerprint; Genomics; Histone Code; Infection; Institution; Knowledge; Malignant Neoplasms; Mass Spectrum Analysis; Mission; Monoclonal Antibodies; Oncogenes; Peptides; Post-Translational Protein Processing; Proteins; Proteomics; Research Infrastructure; Scientist; Services; Software Engineering; Software Tools; Students; System; Techniques; Technology; Testing; Therapeutic; Tissues; Training; base; biomedical scientist; breast cancer vaccine; combinatorial; computerized tools; cost; empowered; human disease; next generation; novel; novel therapeutics; oral microbiome; polyclonal antibody; protein protein interaction; repository; research and development; software development; success; tool

Project Summary Mass spectrometry is based on fragmenting biological molecules into smaller pieces, and using the fragment masses as a fingerprint for identifying and quantifying bio-molecules. It is the dominant technology for studying active molecules in healthy and diseased tissue, and identifying protein targets and natural products for novel therapeutics. When the initial proposal Center for Computational Mass Spectrometry (CCMS) was submitted in 2007, the lack of adequate computational tools for analyzing mass spectrometry data was the the key bottleneck. With great success in enabling applications of new experimental techniques such as FTMS, ETD, HCD, top-down mass spectrometry, and many others, the mandate of CCMS continues to be the development of next generation computational technologies and to apply them to open experimental. In this proposal, we will capitalize on our recent results in diverse subfields of computational proteomics and will further branch into previously unexplored MS applications. We will focus specifically on bridging proteomics and genomics technologies using 6 technology research and development platforms. Specifically, we will (a) apply proteogenomics approach for the discovery of abberant cancer genes and analyzing antibody repertoires; (b) sequence natural antibiotics; (c) collate spectral data through spectral archives and networks; (d) develop universal tools for peptide identification; (e) develop tools for top-down proteomics; and, (f) analyzing multiplexed spectra. The technology platforms are driven by a multitude of collaborative biomedical studies where the use of CCMS developed tools is essential for their success. These studies include (a) unraveling the combinatorial histone code in human diseases; (b) a proteogenomics approach to studies of oral microbiome and polybacterial infections; (c) detecting inter-species chemical interactions; (d) developing a systems approach towards the therapeutic modulation of the acetylome ; (e) developing tools for monoclonal and polyclonal antibody sequencing; (f) development of breast cancer vaccines; (g) clinical cancer proteogenomics; (h) discovery of lantibiotics; (i) discovering proteomic biomarkers for drug toxicity in cancer patients; and, (j) identifying protein-protein interactions and post-translational modifications in cataractous lens. These projects require three-way collaborative efforts on a wide range of topics involving biomedical scientists, mass spectrometrists, and computational scientists from various institutions. CCMS will also train students and practicing scientists from all over the world in computational proteomics, and educate the proteomics community about modern computational mass spectrometry to encourage its wide adoption.

项目总结