Text Mining Point Mutations for Genetic Diagnosis Array

基因诊断阵列的文本挖掘点突变

• 批准号: 6993320
• 负责人: LAWRENCE C LEE
• 金额: $ 4.58万
• 依托单位: UNIVERSITY OF CALIFORNIA, SAN FRANCISCO
• 依托单位国家: 美国
• 财政年份: 2005
• 资助国家: 美国
• 起止时间: 2005-10-01 至 2007-09-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/6993320
• 关键词: biotechnology; information retrieval; microarray technology; molecular biology information system; point mutation; predoctoral investigator; technology /technique development

DESCRIPTION: Text mining applications seek to alleviate the problems with identifying, searching, and extracting relevant information from large sets of literature. The goal of this proposal is to create a text mining application to extract protein point mutations from biomedical literature. The developed application will be used to extract point mutations from literature discussing human genetic disorders, and the retrieved database of point mutations used to design a DNA microarray chip for prenatal genetic diagnosis. First, the text mining application will be developed using machine learning and statistical natural language processing techniques. Second, the point mutation mining application will be applied to a large set of literature related to genetic disorders, and the retrieved point mutations deposited in an electronic database. This collection of point mutations will be examined to find polymorphisms in genes that are markers for genetic disorders. These polymorphic positions in the human genome will be gathered and used to design a DMA microarray chip that can genotype tens of thousands of single nucleotide polymorphisms. The microarray chip can be used for prenatal genetic diagnosis purposes to screen for hundreds of genetic disorders.

产品说明： 文本挖掘应用程序试图缓解从大量文献中识别、搜索和提取相关信息的问题。该提案的目标是创建一个文本挖掘应用程序，从生物医学文献中提取蛋白质点突变。开发的应用程序将被用来提取点突变的文献讨论人类遗传疾病，和检索数据库的点突变用于设计一个DNA微阵列芯片产前基因诊断。首先，将使用机器学习和统计自然语言处理技术开发文本挖掘应用程序。第二，点突变挖掘应用将应用于与遗传疾病相关的大量文献，并且检索到的点突变存储在电子数据库中。将检查这些点突变的集合，以发现作为遗传疾病标记的基因多态性。人类基因组中的这些多态性位置将被收集并用于设计一种DMA微阵列芯片，该芯片可以对数万种单核苷酸多态性进行基因分型。微阵列芯片可用于产前基因诊断目的，以筛选数百种遗传疾病。