CAREER: New Technologies for Querying Pathway Databases

与大多数生物信息学数据（如DNA序列和蛋白质指令）不同，途径显示了不同生物化学实体的相互作用。因此，每个实体或子路径都可以在其路径中具有一个功能，没有它，路径无法实现。表述这些函数提出了令人兴奋的计算挑战。本提案开发了有效和准确的路径计算分析算法。实现这一目标的第一步是建立通路和子通路函数的数学模型。该建议将子通路的功能定义为它对整个通路稳定状态的贡献。计算这种贡献是一个困难的问题，特别是对于基因调控途径。现有的方法可以计算代谢途径，但它们甚至不能扩展到中等大小的基因调节途径。本文提出了计算函数的有效方法。找到具有期望功能的子通路是一个具有挑战性的问题。使用现有工具搜索具有所需功能的子路径没有明确的方法。提出了一种高效的子路径搜索算法。这一建议更进一步，并开发了数学上合理的算法来比较两个路径，以便映射的实体在功能上、同构上和拓扑上相似。本提案还探讨了生物通路数据库的特征和基于参考的索引结构。有关该项目的更多信息可在该项目的网页上找到：http://bioinformatics.cise.ufl.edu/

Unlike most bioinformatics data, such as DNA sequences and proteinstructures, pathways show the interactions of different bio-chemicalentities. Thus, each entity or subpathway can have a function in itspathway that the pathway can not realize without it. Formulating thesefunctions presents exciting computational challenges. This proposal develops algorithms for efficient and accuratecomputational analysis of pathways. The first step in achieving thisgoal is to build a mathematical model for functions of pathways andsubpathways. This proposal defines the function of a subpathway as itscontribution to the steady state of the entire pathway. Computing thiscontribution is a difficult problem especially for gene regulatorypathways. Existing methods can compute this for metabolic pathways,but they do not scale to even medium sized gene regulatorypathways. This proposal develops efficient methods for computingfunction.Finding the subpathway that has a desired function is a challengingproblem. There is no clear way of searching for subpathways withdesired functions using existing tools. This proposal developsefficient algorithms for searching subpathways with desired function.This proposal takes this one step further, and develops mathematicallysound algorithms for comparing two pathways so that the entities thatmap are functionally, homologically and topologically similar. Thisproposal also explores feature and reference-based index structuresfor biological pathway databases.Further information on the project can be found at the project webpage: http://bioinformatics.cise.ufl.edu/