Informatics Center for Neurogenetics and Neurogenomics

这是一份关于加州大学洛杉矶分校神经遗传学和神经基因组信息学中心(ICNN)的NINDS机构中心核心的建议。与生物医学的其他领域一样，后基因组时代带来了神经科学研究取得变革性进展的前景。然而，神经科学在分析、解释和管理由基因和基因组技术产生的大量信息方面面临着特殊的挑战。神经系统的表型和组织复杂性要求不同的分析和信息学战略和专业知识。ICNN将为一个高度互动的用户群体提供高级分析和信息学支持，该用户群体由加州大学洛杉矶分校的神经科学家组成，他们正在进行基础、临床和翻译研究。这些研究人员可以获得优秀的遗传学和基因组学实验设施；在分析和信息学方面缺乏相应的资源构成了他们研究的瓶颈。ICNN学院在统计遗传学、基因表达分析和生物信息学方面的专家将监督训练有素的工作人员的活动，他们将实现三个目标：1)为神经遗传学和神经基因组学项目提供专家咨询和分析；2)开发和维护共享的计算资源，其中将包括用于计算密集型分析的计算集群、网络服务器和用于各种应用的最先进的软件工具(包括公共数据库的用户友好版本以及将培训ICNN用户使用这些工具的工作站；3)向用户提供分析和信息学方面的实践培训。

This is a proposal for an NINDS Institutional Center Core, the Informatics Center for Neurogenetics and Neurogenomics (ICNN) at UCLA. As with other areas of biomedical science, the post-genome era raises the prospect of transformational advances in neuroscience research. Neuroscience faces special challenges, however, in analysis, interpretation, and management of the vast quantities of information generated by genetic and genomic technologies. The phenotypic and organizational complexity of the nervous system calls for distinct analytical and informatics strategies and expertise. The ICNN will provide advanced analysis and informatics support to a highly interactive user group consisting of neuroscientists at UCLA, who are conducting basic, clinical, and translational research. These investigators have access to excellent facilities for genetics and genomics experimentation; the lack of corresponding resources in analysis and informatics constitutes a bottleneck in their research. ICNN faculty experts in statistical genetics, gene expression analysis, and bioinformatics will oversee the activities of highly-trained staff members who will accomplish three goals: 1) Providing expert consultation and analyses for neurogenetics and neurogenomics projects; 2) Developing and maintaining a shared computing resource that will include a computational cluster for computation-intensive analyses, web-servers and state of the art software tools for a wide range of applications (including user-friendly versions of public databases, as well as workstations on which ICNN users will be trained to employ these tools; 3) Providing hands-on training in analysis and informatics to the users.