Center for Computational Mass Spectrometry
Center for Computational Mass Spectrometry
批准号:
8930716
负责人:
Vineet Bafna
金额:
$135.04万
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 2019-06-30
关键词:
AcetylationAddressAdoptionAlgorithmic SoftwareAlgorithmsAntibioticsAntibodiesAntibody RepertoireArchivesAreaBiologicalBiological FactorsBiological MarkersCancer PatientCataractChemicalsClinicalCommunicable DiseasesCommunitiesComplexComputer softwareDNA SequenceDataDatabasesDental cariesDevelopmentDrug TargetingDrug toxicityEmerging TechnologiesFingerprintGenerationsGenesGenomeGenomicsGoalsGuanine Nucleotide Exchange FactorsHealthHistone CodeHistonesHumanHuman MicrobiomeIndustryInfectionInstitutionLibrariesLinkMalignant NeoplasmsMass Spectrum AnalysisMiningMonoclonal AntibodiesMutationOncogenesPeptidesPost-Translational Protein ProcessingProtein IsoformsProteinsProteomeProteomicsProtocols documentationResearchScientistServicesSoftware ToolsStudentsSystemTechniquesTechnologyTherapeuticTherapeutic antibodiesTissuesTrainingbasebiomedical scientistbreast cancer vaccinecombinatorialcomputerized toolsdrug discoveryhuman diseaseimprovedinstrumentinstrumentationlensmicrobialnext generationnext generation sequencingnovelnovel therapeuticsoral microbiomepolyclonal antibodyprotein aminoacid sequenceprotein protein interactionresearch and developmentresponsesuccesstoolvaccine trial
中文摘要
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英文摘要
DESCRIPTION: 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 col- laborative 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 in- teractions; (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 vac- cines; (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 mod- ifications 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.
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eDyNAmiC - UCSD
-
批准号:10845739
-
项目类别:
-
资助金额:$32.94万
-
财政年份:2022
-
负责人:Vineet Bafna
-
依托单位:
eDyNAmiC - UCSD
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批准号:10622287
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项目类别:
-
资助金额:$26.71万
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财政年份:2022
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负责人:Vineet Bafna
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依托单位:
Graduate Training Program in Bioinformatics
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批准号:10089978
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项目类别:
-
资助金额:$39.01万
-
财政年份:2021
-
负责人:Vineet Bafna
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依托单位:
Software and algorithms for elucidating the structure, function, and evolution of extrachromosomal DNA
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批准号:10704060
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项目类别:
-
资助金额:$61.12万
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财政年份:2021
-
负责人:Vineet Bafna
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依托单位:
Software and algorithms for elucidating the structure, function, and evolution of extrachromosomal DNA
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批准号:10477356
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项目类别:
-
资助金额:$72.84万
-
财政年份:2021
-
负责人:Vineet Bafna
-
依托单位:
Graduate Training Program in Bioinformatics
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批准号:10417008
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项目类别:
-
资助金额:$41.63万
-
财政年份:2021
-
负责人:Vineet Bafna
-
依托单位:
Graduate Training Program in Bioinformatics
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批准号:10612423
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项目类别:
-
资助金额:$42.44万
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财政年份:2021
-
负责人:Vineet Bafna
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依托单位:
Software and algorithms for elucidating the structure, function, and evolution of extrachromosomal DNA
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批准号:10305480
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项目类别:
-
资助金额:$74.91万
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财政年份:2021
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负责人:Vineet Bafna
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依托单位:
Core C- Bioinformatics Core
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批准号:10533741
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项目类别:
-
资助金额:$17.62万
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财政年份:2020
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负责人:Vineet Bafna
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依托单位:
Core C- Bioinformatics Core
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批准号:10154464
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项目类别:
-
资助金额:$12.24万
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财政年份:2020
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负责人:Vineet Bafna
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依托单位:
Core C- Bioinformatics Core
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批准号:10300069
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项目类别:
-
资助金额:$13.23万
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财政年份:2020
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负责人:Vineet Bafna
-
依托单位:
Refining Mendelian disease analysis via detection of clinically relevant repeat variants
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批准号:10205131
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项目类别:
-
资助金额:$57.0万
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财政年份:2018
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负责人:Vineet Bafna
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依托单位:
Refining Mendelian disease analysis via detection of clinically relevant repeat variants
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批准号:10586956
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项目类别:
-
资助金额:$56.98万
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财政年份:2018
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负责人:Vineet Bafna
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依托单位:
Computational methods for detecting patterns of complex genomic variation
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批准号:9198242
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项目类别:
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资助金额:$27.24万
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财政年份:2016
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负责人:Vineet Bafna
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依托单位:
Computational methods for detecting patterns of complex genomic variation
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批准号:9027203
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项目类别:
-
资助金额:$27.52万
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财政年份:2016
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负责人:Vineet Bafna
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依托单位:
Computational methods for detecting patterns of complex genomic variation
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批准号:10320932
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项目类别:
-
资助金额:$30.17万
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财政年份:2016
-
负责人:Vineet Bafna
-
依托单位:
Computational methods for detecting patterns of complex genomic variation
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批准号:10543106
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项目类别:
-
资助金额:$30.1万
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财政年份:2016
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负责人:Vineet Bafna
-
依托单位:
Computational methods for detecting patterns of complex genomic variation
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批准号:10077847
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项目类别:
-
资助金额:$28.95万
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财政年份:2016
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负责人:Vineet Bafna
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依托单位:
Algorithmic strategies for detecting structural variation in genomes
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批准号:8035949
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项目类别:
-
资助金额:$32.17万
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财政年份:2009
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负责人:Vineet Bafna
-
依托单位:
Algorithmic strategies for detecting structural variation in genomes
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批准号:8228154
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项目类别:
-
资助金额:$32.36万
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财政年份:2009
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负责人:Vineet Bafna
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依托单位:
海外基金