SECOND GENERATION EST CLUSTER AND ANALYSIS TOOLS

第二代EST集群和分析工具

• 批准号: 6017182
• 负责人: TODD M SMITH
• 金额: $ 10.65万
• 依托单位: GEOSPIZA, INC.
• 依托单位国家: 美国
• 财政年份: 1999
• 资助国家: 美国
• 起止时间: 1999-09-01 至 2000-02-29
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/6017182
• 关键词: computer assisted sequence analysis; computer program /software; computer system design /evaluation; data management; gene expression; genetic markers; genetic polymorphism; genome; informatics; molecular biology information system; nucleic acid sequence

The human genome is estimated to comprise approximately 100,000 genes. However, only a fraction of this total are active in a given cell type at any time. Systematic categorization of Expressed Sequence Tags (ESTs) by clustering and annotation play important roles in understanding normal homeostasis and disease processes. EST clustering involves assembling large data sets of sequences and is complicated by the variability and complexity of sequences that originate from highly similar genes or have alternate forms due to RNA splicing. A complete solution for EST clustering requires software components that are used to organize, assemble, validate, view and annotate individual sequences and sets of data. Currently EST analysis is limited to laboratories that can afford computer specialists and is beyond the reach of most scientists. Geospiza proposes to develop widely available solutions for EST clustering that incorporate quality information and comparative analyses to distinguish biological variation from experimental error and detect alternatively spliced messages. Viewers and interfaces for expression analysis and curating sets of clusters for measuring clustering accuracy will also be designed and prototyped. Performance and accuracy of clustering strategies will be evaluated in a model system studying prostate cancer. PROPOSED COMMERCIAL APPLICATION Methods for EST clustering and analysis are in high demand. Automatically detecting variation in ESTs has numerous applications in drug development, basic research, and clinical studies. Side benefits from scaling Geospiza s existing technology to store millions of chromatogram data files present opportunities for services to support the research community. New databases and information resources will also become possible such as databases of splice variation. Lessons learned developing the prostate model system will have, by analogy, direct application other areas of cancer biology.

人类基因组估计包含约100,000个基因。 但是，在任何时候，在给定的单元格类型中只有一小部分是活动的。 通过聚类和注释对表达的序列标签（EST）进行系统分类，在理解正常的体内稳态和疾病过程中起着重要作用。 EST聚类涉及组装大型序列数据集，并且由于源自高度相似基因或由于RNA剪接而具有替代形式的序列的可变性和复杂性使其复杂化。 用于EST聚类的完整解决方案需要用于组织，组装，验证，查看和注释单个序列和数据集的软件组件。 目前的分析仅限于可以负担得起计算机专家的实验室，并且超出了大多数科学家的范围。 Geospiza建议开发广泛可用的解决方案，以结合质量信息和比较分析，以区分生物学变异与实验误差并检测到替代剪接的消息。 还将设计和原型设计用于测量聚类精度的簇的表达分析和策划集簇集的界面。将在研究前列腺癌的模型系统中评估聚类策略的性能和准确性。提出的用于EST聚类和分析的商业应用方法的需求很高。自动检测EST的变化在药物开发，基础研究和临床研究中有许多应用。 从缩放Geospiza的现有技术中，侧面有益于存储数百万个色谱数据文件，为支持研究社区提供了机会。新的数据库和信息资源也将成为可能，例如剪接变化的数据库。 开发前列腺模型系统开发的经验教训将通过类比直接应用癌症生物学的其他领域。