SUPERCOMPUTING IN OPTIMISATION OF TRANSCRIPTION FACTOR BINDING SITE SEQUENCE AN

超级计算优化转录因子结合位点序列

• 批准号: 8364379
• 负责人: DAVID GHOSH
• 金额: $ 0.11万
• 依托单位: CARNEGIE-MELLON UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-09-15 至 2013-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8364379
• 关键词: Address; Binding Sites; Bioinformatics; Biology; Biomedical Research; Cell Nucleus; Cells; Complex; Databases; Development; Funding; Gene Expression Regulation; Genetic Transcription; Genome; Grant; High Performance Computing; Informatics; Life; Methods; National Center for Research Resources; Organism; Principal Investigator; Protein Family; Proteins; Research; Research Infrastructure; Resources; Signal Pathway; Source; Supercomputing; Technology; United States National Institutes of Health; Work; cost; extracellular; improved; relational database; transcription factor

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. Primary support for the subproject and the subproject's principal investigator may have been provided by other sources, including other NIH sources. The Total Cost listed for the subproject likely represents the estimated amount of Center infrastructure utilized by the subproject, not direct funding provided by the NCRR grant to the subproject or subproject staff. Transcription factors have a variety of complex informatics aspects. In living cells, these proteins are at the endpoint of signaling pathways and transduce extracellular information to the transcription machinery in the nucleus. TFs are among the largest families of proteins encoded by an organism's genome, and thus constitute an important part of gene regulation biology. Managing transcription factor information also offers a variety of challenges which can be addressed by existing database and bioinformatics methods and technologies, as well as those in development. This activity builds on previous work with TFD (Transcription Factors Database), initially organized as a relational database, and technologies to improve database contents as well as to perform computational analyses using information in this database.

这个子项目是利用资源的许多研究子项目之一。 由NIH/NCRR资助的中心拨款提供。对子项目的主要支持 子项目的首席调查员可能是由其他来源提供的， 包括美国国立卫生研究院的其他来源。为子项目列出的总成本可能 表示该子项目使用的中心基础设施的估计数量， 不是由NCRR赠款提供给次级项目或次级项目工作人员的直接资金。 转录因子具有多种复杂的信息学方面。在活细胞中，这些蛋白质处于信号通路的终点，将细胞外信息转导到细胞核内的转录机器。转录因子是生物体基因组编码的最大的蛋白质家族之一，因此构成了基因调控生物学的重要组成部分。管理转录因子信息也带来了各种挑战，这些挑战可以通过现有的数据库和生物信息学方法和技术以及正在开发的方法和技术来解决。这项活动建立在TFD(转录因子数据库)以前工作的基础上，TFD最初被组织为一个关系数据库，以及改进数据库内容和利用该数据库中的信息进行计算分析的技术。