课题基金 / 基金详情

Center for Computational Mass-Spectrometry

Center for Computational Mass-Spectrometry
计算质谱中心
批准号:
8109831
负责人:
Pavel A Pevzner
金额:
$105.24万
依托单位国家:
美国
项目类别:
财政年份:
2008
资助国家:
美国
项目状态:
已结题
起止时间:
2008-09-20 至 2013-06-30

项目摘要

项目成果

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中文摘要
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英文摘要
DESCRIPTION (provided by applicant): This application seeks support for a center of excellence in computational mass spectrometry and a national and international resource in the broad area of proteomics. It proposes to enlarge the current research activities, to branch into previously unexplored areas of computational proteomics, and to support multiple collaborative efforts. The proposal addresses the computational bottleneck that affects the entire proteomics community and impairs interpretation of data in thousands of experimental labs around the world. The goal is to bring the modern algorithmic technologies to mass-spectrometry and to build a new generation of reliable open access software tools to support both new development in mass-spectrometry instrumentation and the emerging applications of mass-spectrometry. The proposal focuses on four directions: (i) enabling complex mass spectrometry searches, (ii) analyzing unknown proteomes without protein databases, (iii) analyzing altered proteomes, and (iv) constructing proteogenomic annotations and analyzing pathways. These directions cover both well-studied but still inadequately addressed problems (like search for mutations and post-translational modifications) and unexplored problems for which there are no computational tools currently available (like antibody sequencing or analyzing fusion proteins in cancer). These projects require two-way collaborative efforts on a wide range of topics involving biomedical and computational scientists from various institutions. While many collaborations have been already established at San Diego (UCSD and Burnham Institute), sixteen other US universities, hospitals and biotechnology companies, as well as foreign research institutions at Germany, Singapore, Spain, Sweden, and United Kingdom, we propose to further extend these collaborations by developing robust open access mass spectrometry software that will catalyze the exchanges between experimental and computational researchers in proteomics. The biomedical applications addressed in these collaborative projects include but are not limited to (i) discovery of cancer biomarkers, (ii) elucidation of changes in aged cataractous lens, (iii) understanding how bacteria adjust to antibiotics and other harsh conditions, (iv) addressing the need to constantly reformulate the influenza vaccine to make it efficient, and (v) sequencing of snake venoms that proved instrumental in design of blood clotting drugs. Educational activities in the area of computational proteomics will also be developed, including short courses, a seminar program, an annual conference, and concerted education of students and postdocs.
期刊论文(36)
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会议论文
DOI: 10.1093/bioinformatics/btr208
发表时间: 2011-07-01
期刊: Bioinformatics (Oxford, England)
影响因子: --
作者: [Medvedev P, Scott E, Kakaradov B, Pevzner P]
通讯作者: Pevzner P
DOI: 10.1021/pr800677f
发表时间: 2009-05
期刊: Journal of proteome research
影响因子: 4.4
作者: [Frank AM]
通讯作者: Frank AM
DOI: 10.1021/pr800678b
发表时间: 2009-05
期刊: Journal of proteome research
影响因子: 4.4
作者: [Frank AM]
通讯作者: Frank AM
DOI: 10.1038/ncomms6277
发表时间: 2014-10-31
期刊: NATURE COMMUNICATIONS
影响因子: 16.6
作者: [Kim, Sangtae, Pevzner, Pavel A.]
通讯作者: Pevzner, Pavel A.
16
    DEVELOPMENT OF ONLINE COMPUTATIONAL GENOMICS SPECIALIZATION
    DEVELOPMENT OF ONLINE COMPUTATIONAL GENOMICS SPECIALIZATION
    DEVELOPMENT OF ONLINE COMPUTATIONAL GENOMICS SPECIALIZATION
    Integrated Active Learning Framework for Biomedical BD2K
    国内基金
    海外基金
    Computational Methods for Analyzing Toponome Data