Scalable Secure Sharable Computation Platform for Proteomics Data Analysis
Scalable Secure Sharable Computation Platform for Proteomics Data Analysis
批准号:
7433587
负责人:
ERIK J NILSSON
金额:
$18.86万
依托单位:
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:
2008-05-01 至 2010-04-30
关键词:
AddressAdoptionAffectArtsAttentionBioinformaticsBiologicalBiological MarkersBiomedical ResearchCollaborationsComplexComputer AnalysisComputer softwareComputersDataData AnalysesData SetDatabasesDevelopmentEffectivenessElementsEnvironmentFarming environmentFutureHealth BenefitHourInstitutionIntentionLaboratoriesMainstreamingMaintenanceMass Spectrum AnalysisMeasurementMeasuresOutcomeOwnershipPerformanceProteinsProteomicsPublic HealthRateResearchResearch ActivityResearch InfrastructureResearch PersonnelResearch Project GrantsResourcesRetrievalSamplingSecureSecuritySolutionsSystemTechniquesTechnologyTestingTimeWorkcomparativecomputerized toolscostdata managementinsightnovelopen sourcerepairedresearch studyscientific computingsoftware developmenttoolvirtual
中文摘要
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英文摘要
DESCRIPTION (provided by applicant): A novel distribution platform for an open source proteomic database and computational analysis system is proposed. The proposed platform will enable inter-institutional collaboration in the study of biological mechanisms and measurement of complex protein systems. Installation is an initial and sometimes insurmountable barrier to open source software adoption, especially for state of the art database systems such as CPAS. We propose to create a hosted CPAS server platform to eliminate installation and maintenance issues for both software and hardware, thus increasing the open source bioinformatics tools adoption rate and drastically reducing total cost of ownership for open source bioinformatics tools like CPAS. Virtual cluster technology also offers new solutions to the security, scalability, and ease of use problems that have hampered proteomics collaborations to date. This proposed system builds on a successful collaboration of experts in proteomics and software development, and marks the one of the first major use of virtual cluster technology in proteomics. PUBLIC HEALTH RELEVANCE: The aim of this research is to enable a new proteomics technology that will both lower the cost of proteomics experiments and lower the barriers to collaboration between research institutions. A successful outcome would increase the potential health benefit of a broad array of current and future research.
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