Novel algorithms and organisms for Onto-Tools

描述（由申请人提供）：分子生物学和遗传学目前处于信息革命的中心。高吞吐量技术会生成大量的异构数据。我们收集数据的能力和解释数据的能力之间存在巨大差距。当今研究人员面临的挑战是开发有效的方法来分析已经收集并将继续收集的大量数据。Onto-Tools于2001年首次发布，是一个开放获取的软件套件，部分解决了这个问题。这是通过使用概率功能分析来实现的，该概率功能分析弥合了低水平、高通量基因表达数据与高水平功能知识之间的差距。该建议通过开发基于潜在语义索引和统计分析的新数据分析技术进一步解决了现有的计算挑战。这些技术将能够在基因水平上发现以前未知的相互作用和现象。使用这种方法可以发现新的基因间相互作用、新的基因功能分配以及生物过程之间的干扰相互作用。大多数试图预测基因功能的技术依赖于具有已知功能的基因，并使用序列相似性、3D结构相似性或两者来推断新基因的功能。我们的方法是创新的，因为它使用真实的表达数据来提取目标基因的功能。拟议的工具Onto-Analyzer将作为Onto-Tools套件的一部分提供这些功能。Onto-Tools还将通过增加对17种新生物的支持而得到增强。开发先进计算工具的目标也受到当前知识的另一个差距的阻碍。成功的公共生物信息学软件拥有庞大而苛刻的用户群体。为了从根本上改进软件，同时保持预期的服务水平，通常需要大量的资源，而这些资源是小型研究小组无法获得的。因此，迁移到开源平台是可取的。为了实现这种迁移，Onto-Tools的可演化性、可修复性、可修改性、可移植性、可理解性和文档将得到改进。该研究将开发一套软件演化工具，通过软件，可视化，变更影响分析，可追溯性链接恢复和重新文档化来解决这些问题。增强的Onto-Tools将继续免费提供。Onto-Analyzer和根据该提案开发的软件演化工具也将免费提供给研究界。

DESCRIPTION (provided by applicant): Molecular biology and genetics are currently at the center of an information revolution. High-throughput techniques generate very large amounts of heterogeneous data. There is a large gap between our ability to collect data and our ability to interpret it. The challenge faced by today's researchers is to develop effective ways to analyze the vast amount of data that has been and will continue to be collected. First released in 2001, Onto-Tools is an open access software suite that partially addresses this problem. This is achieved by using a probabilistic functional analysis that bridges the gap between low-level, high-throughput gene expression data and high-level functional knowledge. This proposal further addresses the existing computational challenge by developing novel data analysis techniques based on latent semantic indexing and statistical analysis. These techniques will be able to discover previously unknown interactions and phenomena at the genetic level. New gene-to-gene interactions, novel gene-to-function assignments, and perturbed interactions between biological processes can be discovered using this approach. Most techniques that try to predict gene functions rely on genes with known function and use sequence similarity, 3D structure similarity, or both, to extrapolate the functionality of novel genes. Our approach is innovative because it uses real expression data to extract the functions of the target genes. The proposed tool, Onto-Analyzer, will offer these capabilities as part of the Onto-Tools suite. Onto-Tools will also be enhanced by adding support for 17 new organisms. The goal of developing advanced computational tools is also obstructed by another gap in the current knowledge. Successful public bioinformatics software has a large and demanding user community. To radically evolve software and, at the same time, to maintain the expected level of service usually requires large resources, unavailable to small research groups. Therefore migration to open source platform is desirable. In order to enable this migration, the evolvability, reparability, modifiability, portability, understandability, and the documentation of Onto-Tools will be improved. The proposed research will develop a set of software evolution tools to address these issues trough software, visualization, change impact analysis, traceability link recovery, and re-documentation. The enhanced Onto-Tools will continue to be freely available. Onto-Analyzer and the software evolution tools developed under this proposal will be made freely available to the research community, as well.