BIOINFORMATICS

生物信息学

• 批准号: 8559551
• 负责人: Michael F Ochs
• 金额: $ 30.8万
• 依托单位: JOHNS HOPKINS UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 1997
• 资助国家: 美国
• 起止时间: 1997-05-07 至 2017-04-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8559551
• 关键词: Bioinformatics; Bioinformatics Shared Resource; Biological; Cancer Center; Cancer Center Support Grant; Clinical; Collaborations; Comprehensive Cancer Center; Computer Simulation; Data; Data Analyses; Data Set; Data Storage and Retrieval; Detection; Development; Developmental Process; Doctor of Philosophy; Epigenetic Process; Faculty; Funding; Genomics; Imagery; Malignant Neoplasms; Maps; Methodology; Methylation; Mission; Modeling; Molecular; Morphologic artifacts; Pathway Analysis; Pathway interactions; Play; Postdoctoral Fellow; Proteomics; Quality Control; RNA; Research; Research Design; Research Personnel; Resources; Role; Sequence Analysis; Statistical Models; Sulfites; Systems Analysis; Systems Biology; Techniques; Technology; Training; Variant; anticancer research; base; biological systems; data acquisition; epigenomics; experience; genome sequencing; innovation; member; metabolomics; next generation; oncology; success; tool; transcriptomics

The mission of the Bioinformatics Shared Resource (BISR) is to guarantee the availability of comprehensive bioinformatics expertise to Sidney Kimmel Comprehensive Cancer Center (SKCCC) members involved in molecular cancer research, with special emphasis on techniques that generate high dimensional data. The BISR achieves this by partially funding the effort for several PhD-level investigators and related staff. BISR faculty have extensive experience in all aspects of high-throughput biological data analysis and computational modeling of biological systems. A critical development during the next funding period will be the emergence of large data sets comprising multiple omics data, including genomics (SNPs, allelic variation maps from high-throughput sequencing), epigenomics (methylation an-ays, bi-sulfite high-throughput sequencing), transcriptomics (microarrays and RNA-seq), proteomics (MS-MS and arrays), and metabolomics (MS and NMR). These data will require integration through annotations, both through genome sequence and using proteomic-based integration. Computational modeling of this data will play an increasingly important role, as the data could overwhelm mathematical analysis approaches that lack a biologically motivated model to place the data in context Pathway, network, and cellular systems analysis is expected to play a growing role in data interpretation, with systems biology and computational modeling emerging as critical capabilities for the BISR. This Core has been assembled with the breadth in expertise necessary for these developments. Lay: The Bioinformatics Resource provides comprehensive bioinformatics expertise to Cancer Center members involved in molecular cancer research, with special emphasis on techniques that generate high dimensional data. The BISR has several PhD-level investigators with extensive experience in all aspects of high-throughput biological data analysis and computational modeling of biological systems, together with support staff.

生物信息学共享资源(BISR)的使命是保证参与分子癌症研究的Sidney Kimmel综合癌症中心(SKCCC)成员获得全面的生物信息学专业知识，特别强调生成高维数据的技术。BISR通过为几个博士级别的调查人员和相关工作人员的努力提供部分资金来实现这一点。BISR的教师在生物系统的高通量生物数据分析和计算建模的各个方面都有丰富的经验。下一个供资期间的一个关键发展将是出现包含多种组学数据的大型数据集，包括基因组学(SNPs，来自高通量测序的等位基因变异图)、表观基因组学(甲基化分析、亚硫酸盐高通量测序)、转录组学(微阵列和RNA-seq)、蛋白质组学(MS-MS和阵列)和代谢组学(MS和核磁共振)。这些数据将需要通过注释进行整合，包括通过基因组序列和使用基于蛋白质组的整合。这些数据的计算建模将发挥越来越重要的作用，因为数据可能会压倒数学分析方法，这些方法缺乏生物动机的模型来将数据置于上下文中。路径、网络和蜂窝系统分析预计将在数据解释中发挥越来越大的作用，系统生物学和计算建模将成为BISR的关键能力。这一核心已与这些发展所需的广泛专业知识组装在一起。Lay：生物信息学资源为参与分子癌症研究的癌症中心成员提供全面的生物信息学专业知识，特别强调生成高维数据的技术。BISR有几个博士级别的调查人员，他们在高通量生物数据分析和生物系统计算建模的各个方面都有丰富的经验，还有支持人员。