SOFTWARE FOR EVOLUTION BASED FUNCTIONAL GENOMICS

“功能生物信息学”中的第一阶段SBIR计划将测试从基因组序列数据中提取功能信息的可行性，该数据库是一个根据蛋白质序列的“自然”组织(它们产生的进化历史)排列的数据库，并通过多序列比对、进化树和重建的祖先序列描述序列模块家族，使用三个软件工具：(A)通过将进化树根附近的概率祖先序列比对来检测蛋白质家族之间远距离同源性的工具。(B)通过比较预测的各个家族的二级结构模型来检测蛋白质家族之间的远距离同源性的工具。(C)使用重建蛋白质家族树中的祖先序列并检测它们之间快速序列进化的方法，识别蛋白质家族进化史中功能可能发生变化的片段的工具。这项可行性测试将针对现有基因组数据库中的所有蛋白质序列全面应用这些工具。如果它们能被证明对分析基因组序列数据库中的功能差异普遍有用，它们将被纳入第二阶段的商业包中，帮助生物科学家从基因组数据库中得出关于生物功能的推断。拟议的商业应用：制药公司、生物技术公司、基因组公司、联邦机构和学术机构都需要软件来解释和使用来自基因组测序项目的海量蛋白质序列数据。本研究将开发这些软件工具。

This Phase I SBIR program in "functional bioinformatics" will test the feasibility of extracting functional information from genome sequence data starting from a rectified database, one that arrange protein sequences according to their "natural" organization (the evolutionary history by which they arose), and describes families of sequence modules by multiple sequence alignments, evolutionary trees, and reconstructed ancestral sequences, using three software tools: (a) Tools that detect distant homology between protein families by aligning probabilistic ancestral sequences near the root of the evolutionary tree. (b) Tools that detect distant homology between protein families by comparing predicted secondary structure models of individual families. (c) Tools that identify episodes in the evolutionary history of a protein family where function might have changed, using methods that reconstruct ancestral sequences in a protein family tree and detect episodes of rapid sequence evolution between them. This feasibility test will apply these tools comprehensively against all protein sequences in the extant genomic database. If they can be shown to be generally useful for analyzing functional divergence within genomic sequence databases, they will be incorporated in Phase II into a commercial package that helps the biological scientist draw inferences about biological function from the genomic database. PROPOSED COMMERCIAL APPLICATIONS: Pharmaceutical companies, biotechnology companies, genomics companies, Federal agencies, and academic institutions all need software to allow them to interpret and use the enormous volumes of protein sequence data that are coming from genome sequencing projects. This research will develop these software tools.