Informatic profiling of clinically relevant mutation

临床相关突变的信息分析

基本信息

批准号：
8328943
负责人：
SEAN DAVID MOONEY
金额：
$ 46.15万
依托单位：
BUCK INSTITUTE FOR RESEARCH ON AGING
依托单位国家：
美国
项目类别：
财政年份：
2007
资助国家：
美国
起止时间：
2007-09-30 至 2015-08-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/8328943
关键词：
Affect Algorithms Amino Acid Substitution Area Bioinformatics Biomedical Research Classification Code Collaborations Complex Computer software DNA Resequencing Data Data Set Disease Disease Association Disease model Feedback Focus Groups Functional RNA Funding Gene Expression Regulation Genes Genetic Genetic Polymorphism Genetic Sequence Databases Genome Genomics Genotype Goals Hereditary Disease Human Human Genome Individual Informatics Inherited Internet Laboratories Leadership Left Letters Machine Learning Malignant Neoplasms Meta-Analysis Methods Modeling Molecular Mutation Mutation Analysis Paper Performance Pharmacogenetics Phenotype Process Proteins Publishing Research Research Personnel Research Proposals Resources Role Science Scientist Staging Structure System Testing Transcript Untranslated Regions Variant Work base cancer genome career clinically relevant data management disease phenotype disease-causing mutation exome genetic regulatory protein genetic variant genome database genome sequencing human disease improved innovation multidisciplinary novel novel strategies protein structure function software development tool user-friendly

项目摘要

DESCRIPTION (provided by applicant): Our group focuses on genetic variants that disrupt molecular functions that cause human disease. In this renewal R01 application, we propose to begin the process of realizing our long-term goals, and to expand our original scope of research to include the challenge of understanding genetic disease mutations and polymorphisms that affect gene expression regulation in noncoding regions. Additionally, we have formed collaborations with genetic data managers and will apply these methods to aid in their research and identify new testable hypotheses. We will do this in three aims. First, we will integrate predictions of protein-disease associations with mutation predictions to develop a new quantitative model of genotype and phenotype. Second, we will integrate each of these together to develop a systems level, molecular function genome annotator with functionality to import into the genome databases. Finally, we will continue to build new methods for characterization of mutations using sequence, function and structure and begin testing our published hypotheses. Each of these aims will include collaboration with the maintainers of genetic datasets to better understand their underlying molecular effects.

描述（由申请人提供）：我们的小组专注于破坏引起人类疾病的分子功能的遗传变异。在此续签R01应用中，我们建议开始实现我们的长期目标的过程，并扩大我们的原始研究范围，以包括了解影响非编码区域基因表达调节的遗传疾病突变和多态性的挑战。此外，我们已经与遗传数据经理建立了合作，并将应用这些方法来帮助他们的研究并确定可检验的新假设。我们将以三个目标来做到这一点。首先，我们将将蛋白质 - 疾病关联的预测与突变预测相结合，以开发一种新的基因型和表型的定量模型。其次，我们将将每一个集成在一起，以开发系统级别的分子功能基因组注释器具有功能，以导入基因组数据库。最后，我们将继续构建使用序列，功能和结构来表征突变的新方法，并开始检验我们已发表的假设。这些目标中的每一个都将包括与遗传数据集维护者的合作，以更好地了解其潜在的分子效应。