CSHL HUMAN GENOME INFORMATICS RESEARCH RESOURCE

从人类基因组计划产生的方法和材料非常适合满足 人类遗传疾病研究中的挑战（包括 易感风险和自发突变），这需要有能力 检测和整理异质性、多基因和上位性遗传 影响，受环境因素影响。 我们的论点是， 查找和功能分析可以大大加快使用状态- 最先进的计算机方法，如果（1）相关数据被表示为 以简单、可重复和综合的方式，（2） 这些数据在小型假设驱动的研究实验室之间的流动， 优化大基因组中心，（3）增强基础研究人员的能力 使用“用户友好”但技术强大的工具， 数据的解释。 因此，我们建议扩大我们的工作， 在这样一个系统上，基因组地形图仪（GT）。 具体而言，目标 这一NCHGR P41补助金是：1。优化GT用户的能力 收集和合并高度详细的基因，分子和生物化学 来自主要基因组中心的数据，各种公共数据库（例如， GenBank，GDB，CHLC，小鼠基因组数据库，各种基于ACeDB的文件）， 和科学文献。 2.将最先进的 GT框架内的序列分析和解释工具，称为 序列分析员（SA）。 SA旨在帮助用户执行和 使用已知的方法解释敏感的序列分析， 数学上最优，同时保持与现有 方法，如BLAST和FASTA。 3.为了提供足够的服务， 培训和文件，以确保研究人员迅速获得 社区的技术和信息在此描述。

The methods and materials resulting from the HGP are well suited to meet the challenges in the study of human genetics diseases (including predisposed risk and spontaneous mutations), which require the ability to detect and sort out heterogeneous, polygenic, and epistatic genetic effects, modulated by environmental factors. It is our thesis that gene finding and functional analysis could be greatly accelerated using state- of -the art computer methodologies if (1) relevant data were represented in a simple, reproducible and integrated manner, (2) the timeliness of the flow of such data between small, hypothesis driven research labs and large genome centers was optimized, (3) basic researchers were empowered with"user-friendly", but technically powerful, tools for computer-aided interpretation of the data. Therefore, we propose to scale up our work on such a system, the Genome Topographer (GT). Specifically, the aims of this NCHGR P41 grant are: 1. To optimize the ability of users of GT to gather and merge highly detailed genetic, molecular and biochemical data from the major genome centers, various public databases (e.g. GenBank, GDB, CHLC, Mouse Genome Database, various ACeDB-based files), and the scientific literature. 2. To integrate a state-of-the-art sequence analysis and interpretation tool within the GT framework, called Sequence Analyst (SA). SA is designed to help the user perform and interpret sensitive sequence analyses using methods that are known to be mathematically optimal, while remaining compatible with existing approaches, such as BLAST and FASTA. 3. To provide adequate services, training and documentation to ensure rapid access by the research community to the technology and information described herein.