Novel Algorithms & Organisms for Onto-Tools

描述(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。高吞吐量技术会产生非常大量的异类数据。我们收集数据的能力和解读数据的能力之间存在着很大的差距。今天的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海量数据。On-Tools于2001年首次发布，它是一个开放访问软件套件，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，该分析弥合了低水平、高通量的基因表达数据和高级功能知识之间的差距。该提案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层面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到基因的相互作用，新的基因到功能的分配，以及生物过程之间的扰动相互作用。大多数试图预测基因功能的技术依赖于已知功能的基因，并使用序列相似性或3D结构相似性，或两者兼而有之，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On-Analyzer将作为On-Tools套件的一部分提供这些功能。通过增加对17个新生物体的支持，Onto-Tools也将得到加强。开发先进计算工具的目标也被当前知识中的另一个鸿沟所阻碍。成功的公共生物信息学软件拥有一个庞大且要求苛刻的用户社区。要从根本上发展软件，同时保持预期的服务水平，通常需要大量资源，而小型研究团队无法获得这些资源。因此，向开源平台迁移是可取的。为了实现这一迁移，将改进Onto-Tool的可进化性、可修复性、可修改性、可移植性、可理解性和文档。拟议的研究将开发一套软件演变工具，通过软件、可视化、变更影响分析、可追溯性链接恢复和重新编制文档来解决这些问题。增强的OntTool将继续免费提供。OTO-Analyzer和根据这一提议开发的软件演变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.