A Unified High Performance Web Service for Systems Genetics and Precision Medicine

用于系统遗传学和精准医学的统一高性能 Web 服务

• 批准号: 10454353
• 负责人: Pjotr Prins
• 金额: $ 42.9万
• 依托单位: UNIVERSITY OF TENNESSEE HEALTH SCI CTR
• 依托单位国家: 美国
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-04-15 至 2025-06-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10454353
• 关键词: Animal Model; Area; Bioinformatics; Biological Models; Biology; Caenorhabditis elegans; Candidate Disease Gene; Code; Communities; Community Participation; Complex; Computer software; Computing Methodologies; Data; Data Analyses; Data Collection; Data Scientist; Data Set; Databases; Drosophila genus; Equilibrium; Experimental Genetics; FAIR principles; Foundations; Funding; Generations; Genes; Genetic; Genetic Diseases; Genetic Medicine; Genetic study; Genomics; Genotype; Goals; Health; Human; Human Genetics; Internet; Joints; Knowledge; Linear Models; Link; Machine Learning; Medical Genetics; Metadata; Methods; Modeling; Molecular; Motivation; Multiomic Data; Mus; National Institute of General Medical Sciences; Online Systems; Ontology; Organism; Pathway Analysis; Performance; Phenotype; Population; Population Heterogeneity; Positioning Attribute; Programming Languages; Pythons; Quality Control; Randomized; Rattus; Reproducibility; Research; Research Personnel; Resources; Role; Sample Size; Science; Secure; Ships; Site; Solid; Structure; Synteny; System; Testing; Time; Tissues; Translations; Trust; United States National Institutes of Health; Variant; addiction; causal model; cohort; computerized tools; data curation; data reuse; data sharing; data tools; data visualization; disorder risk; experimental study; genetic analysis; genome wide association study; genomic data; high throughput analysis; high throughput technology; improved; innovation; insight; pan-genome; precision medicine; prototype; simulation; skills; statistics; tool; trait; translational genetics; web services

High-throughput technologies have transformed biology by enabling deep phenotyping of living organisms. Deep phenotyping in genetically randomized populations provides a powerful resource for understanding cause and effect – this is the promise of systems genetics and precision medicine. Despite the advances in data collection and the availability of genetic and genomic resources, generation of actionable knowledge from these data presents computational and statistical challenges. The goal of the GeneNetwork project is to provide a platform of innovation to make the best use of the data and computational tools for systems genetics. The proposed project will focus on broadening the impact of the web service by broadening community participation in the web service and strengthening computational engine powering the web service. We will enhance our database by providing automated tools for data entry and curation (Aim 1); we will improve tools for genetic analysis of high-throughput traits (Aim 2); enable bidirectional information sharing between animal model and human genetic studies (Aim 3); and provide a platform for toolset prototying and testing by the computational community (Aim 4).

高通量技术通过实现活生物体的深度表型，改变了生物学。