CSHL HUMAN GENOME INFORMATICS RESEARCH RESOURCE

由人类基因组计划产生的方法和材料非常适合满足 人类遗传性疾病研究面临的挑战(包括 易患风险和自发突变)，这需要能力 检测和分类异质性、多基因和上位性遗传 受环境因素调节的影响。这是我们的论文，基因 使用状态-可以极大地加速查找和功能分析 最先进的计算机方法，如果(1)表示了相关数据 以一种简单、可重复和综合的方式，(2) 这类数据在小型、假设驱动的研究实验室和 优化了大的基因组中心，(3)基础研究人员得到了授权 使用“用户友好的”但技术上强大的计算机辅助工具 对数据的解释。因此，我们建议扩大我们的工作 在这样的系统上，基因组拓扑仪(GT)。具体地说，目标是 这笔NCHGR P41赠款包括：1.优化GT用户的能力 收集和合并非常详细的遗传、分子和生化 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)、 以及科学文献。2.集成最先进的 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序列分析 数学上最优，同时保持与现有的兼容 方法，如BLAST和FASTA。3.提供足够的服务， 培训和文档，以确保研究的快速访问 社区对这里描述的技术和信息。

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.