Novel Algorithms & Organisms for Onto-Tools

新颖的算法

• 批准号: 7127247
• 负责人: SORIN DRAGHICI
• 金额: $ 29.29万
• 依托单位: WAYNE STATE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2005
• 资助国家: 美国
• 起止时间: 2005-09-26 至 2008-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7127247
• 关键词: bioinformatics; computer program /software; computer system design /evaluation; functional /structural genomics; gene interaction; information display

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.

描述（由申请人提供）：分子生物学和遗传学目前是信息革命的中心。高通量技术会产生大量的异质数据。我们收集数据的能力与解释数据的能力之间存在很大差距。当今研究人员面临的挑战是开发有效的方法来分析已经并且将继续收集的大量数据。 TOOL Tools于2001年首次发布，是一个开放式访问软件套件，部分解决了此问题。这是通过使用概率功能分析来实现的，该功能分析弥合了低水平，高通量基因表达数据和高级功能知识之间的差距。该建议通过基于潜在语义索引和统计分析来开发新颖的数据分析技术进一步解决了现有的计算挑战。这些技术将能够在遗传水平上发现以前未知的相互作用和现象。可以使用这种方法发现新的基因与基因相互作用，新的基因到功能分配和生物过程之间的扰动相互作用。试图预测基因功能的大多数技术都取决于具有已知功能和使用序列相似性，3D结构相似性的基因，或者两者都可以推断新基因的功能。我们的方法具有创新性，因为它使用实际表达数据来提取目标基因的功能。所提出的工具，即安分析仪，将提供这些功能，作为工具套件的一部分。通过增加对17种新生物的支持，也将增强上工具。当前知识中的另一个差距也阻碍了开发高级计算工具的目标。成功的公共生物信息学软件具有庞大且苛刻的用户社区。从根本上发展软件，同时维持预期的服务水平通常需要大量资源，而小型研究小组无法获得。因此，需要迁移到开源平台。为了启用这种迁移，将改善可变性，可偿还性，可修改性，可移植性，可理解性和通往工具的文档。拟议的研究将开发一套软件演化工具，以解决这些问题，可视化，变化影响分析，可追溯性链接恢复和重新介绍。增强的上工具将继续免费提供。在本提案下开发的软件分析仪和软件演化工具也将免费提供给研究社区。