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.
