CORE--GENOMICS /BIOINFORMATICS--ALZHEIMER'S DISEASE AND AUTISM

核心--基因组学/生物信息学--阿尔茨海默病和自闭症

• 批准号: 7914469
• 负责人: Thomas Conrad GILLIAM
• 金额: $ 13.63万
• 依托单位: COLUMBIA UNIVERSITY HEALTH SCIENCES
• 依托单位国家: 美国
• 资助国家: 美国
• 起止时间: 至
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/7914469
• 关键词: Academia; Alzheimer' s Disease; Area; Autistic Disorder; Bioinformatics; Candidate Disease Gene; Computational Biology; Computer software; Computing Methodologies; Data Set; Development; Discipline; Disease; Educational workshop; Environment; Faculty; Family; Genes; Genetic; Genetic Determinism; Genetic Variation; Genomics; Genotype; Goals; Individual; Industry; Literature; Methods; Ontology; Pathway interactions; Postdoctoral Fellow; Predisposition; Process; Proteins; Scientist; Training; Training Programs; Universities; Work; base; data mining; design; genetic variant; graduate student; improved; kindred; member; novel; post-doctoral training; programs; sample collection; tool

The goal of the proposed studies is to inform and enhance the search for genetic determinants of common, heritable disease by predicting novel candidate genes, and pathways of interacting gene products, likely to harbor genetic variation that influences susceptibility to, or protection against, development of disease. This study will provide a conduit of candidate genes, and gene-networks, that will be genotyped in large, family-based sample collections of Alzheimer's Disease (AD) and autism plus spectrum disorder (ASD) kindreds, respectively. A second goal is to design and apply appropriate statistical and computational methods to analyze the type of novel genetic datasets that will emerge from the proposed studies, and to identify disease related genetic variants. This will require extensive use of evidence integration methods, biomedical literature datamining, and ontologies developed in Cores 9001 and 9002.

拟议研究的目标是通过预测新的候选基因和相互作用的基因产物的途径，为寻找常见的遗传性疾病的遗传决定因素提供信息和加强搜索，这些基因产物可能含有影响疾病易感性或预防疾病发展的遗传变异。这项研究将提供一个候选基因和基因网络的管道，这些基因将分别在阿尔茨海默病（AD）和自闭症加谱系障碍（ASD）kinetics的大型基于家族的样本集合中进行基因分型。第二个目标是设计和应用适当的统计和计算方法来分析将从拟议研究中出现的新型遗传数据集的类型，并识别疾病。 相关的遗传变异。这将需要广泛使用证据整合方法，生物医学文献数据挖掘，以及在核心9001和9002开发的本体。