Data Integration and Disease Risk Modeling in the Context of Molecular Networks
分子网络背景下的数据集成和疾病风险建模
基本信息
- 批准号:8936055
- 负责人:
- 金额:--
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2011
- 资助国家:美国
- 起止时间:2011-09-22 至 2016-07-31
- 项目状态:已结题
- 来源:
- 关键词:AccountingAffectArchitectureAutistic DisorderBindingBiologicalBiological AssayBipolar DisorderCatalogingCatalogsCharacteristicsChicagoClinicalComplexComputer softwareDNADataDatabasesDevelopmentDiseaseDrug PrescriptionsEnvironmental Risk FactorFrequenciesGene ExpressionGene ProteinsGenesGeneticGenetic PolymorphismGenetic RecombinationGenotypeHumanHuman GenomeInformation NetworksInstructionInternetKnowledgeLearningLocationMental DepressionMetabolicMethylationModelingMolecularMolecular BiologyMolecular ProfilingPathway interactionsPhenotypePopulation CharacteristicsProcessProteinsQuality ControlResearchRiskSchizophreniaSingle Nucleotide PolymorphismStatistical AlgorithmStatistical MethodsSystemTechnologyTreatment outcomeUniversitiesVariantbasecomparative genomic hybridizationdata acquisitiondata integrationdata miningdisorder riskgenetic variantgenome annotationgenome-widehigh throughput technologyhuman diseasemathematical modelneuropsychiatrynovel
项目摘要
Advances-in molecular biology that have enabled the development of high throughput technologies for
assaying gene expression, very large numbers of single nucleotide polymorphisms (SNPs), proteins,
metabolic profiles etc. have revolutionized our ability to understand the biological basis of complex human
disorders. As a consequence, we have now developed gene expression profiles that can predict treatment
outcomes, and identified SNPs that are reproducibly associated with complex human diseases, findings that
had previously been all but intractable. But it is difficult to be satisfied with the progress we have made when
there is still so much that we do not know or understand about how common disorders arise and develop.
We believe that we can learn much more from the systematic organization of the totality of the information
developed through genome-wide interrogation of gene expression and DNA polymorphism than we have yet
appreciated. Thus we propose to focus our expertise in statistical methods and algorithms for mining the
data generated from genome-wide platforms toward a better understanding of the molecular architecture of
psychiatric phenotypes. We will achieve this through a dynamic process of data acquisition, integration,
phenotype deconstruction, and the development of a database, software and associated web browser that
should provide the next logical step in merging the information that has started to become available from
large throughput genotyping , sequencing, comparative genomic hybridization, and expression technology.
The database will contain detailed annotation of all known genetic variants (including general information on
location, conservation and local recombination rates, population characteristics such as frequency and
evidence for selection, as well as association data on clinical and expression phenotypes), and of all genes
(including general characteristics of location and variants within, information on pathways associated to the
gene, as well as known SNPs and phenotypes associated with the gene). This project will build on an
existing effort at University of Chicago called SCAN (SNP and CNV Annotation Network, www.scandb.org).
分子生物学的进步促进了高通量技术的发展
分析基因表达、大量单核苷酸多态性 (SNP)、蛋白质、
代谢谱等彻底改变了我们理解复杂人类生物学基础的能力
失调。因此,我们现在开发了可以预测治疗的基因表达谱
结果,并确定了与复杂人类疾病可重复相关的 SNP,研究结果
以前几乎是棘手的。但很难对我们所取得的进展感到满意
对于常见疾病是如何产生和发展的,我们还有很多不了解或不了解的地方。
我们相信,我们可以从全部信息的系统组织中学到更多东西
通过对基因表达和 DNA 多态性进行全基因组询问而开发出来的
赞赏。因此,我们建议将我们的专业知识集中在统计方法和算法上,以挖掘
从全基因组平台生成的数据可以更好地理解基因的分子结构
精神表型。我们将通过数据采集、集成、
表型解构,以及数据库、软件和相关网络浏览器的开发
应该提供下一个逻辑步骤来合并已开始可用的信息
大通量基因分型、测序、比较基因组杂交和表达技术。
该数据库将包含所有已知遗传变异的详细注释(包括有关
位置、保护和局部重组率、种群特征,例如频率和
选择的证据,以及临床和表达表型的关联数据)以及所有基因
(包括位置的一般特征和变异,与相关路径的信息
基因,以及已知的 SNP 和与该基因相关的表型)。该项目将建立在
芝加哥大学现有的工作称为 SCAN(SNP 和 CNV 注释网络,www.scandb.org)。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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Nancy J Cox其他文献
Reaching for the next branch on the biobank tree of knowledge
伸手去够生物银行知识之树上的下一个分支
- DOI:
10.1038/ng.3946 - 发表时间:
2017-09-01 - 期刊:
- 影响因子:29.000
- 作者:
Nancy J Cox - 通讯作者:
Nancy J Cox
Nancy J Cox的其他文献
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{{ truncateString('Nancy J Cox', 18)}}的其他基金
Training Program on Genetic Variation and Human Phenotypes
遗传变异和人类表型培训计划
- 批准号:
10420390 - 财政年份:2022
- 资助金额:
-- - 项目类别:
Training Program on Genetic Variation and Human Phenotypes
遗传变异和人类表型培训计划
- 批准号:
10651837 - 财政年份:2022
- 资助金额:
-- - 项目类别:
Polygenic risk scores and health disparities: the role of blood cells immune response and evolutionary adaptation
多基因风险评分和健康差异:血细胞免疫反应和进化适应的作用
- 批准号:
10212768 - 财政年份:2021
- 资助金额:
-- - 项目类别:
Southeast Collaborative for Innovative and Equitable Solutions to Chronic Disease Disparities
东南合作以创新和公平的方式解决慢性病差异
- 批准号:
10891968 - 财政年份:2021
- 资助金额:
-- - 项目类别:
Polygenic risk scores and health disparities: the role of blood cells immune response and evolutionary adaptation
多基因风险评分和健康差异:血细胞免疫反应和进化适应的作用
- 批准号:
10424445 - 财政年份:2021
- 资助金额:
-- - 项目类别:
Southeast Collaborative for Innovative and Equitable Solutions to Chronic Disease Disparities
东南合作以创新和公平的方式解决慢性病差异
- 批准号:
10437309 - 财政年份:2021
- 资助金额:
-- - 项目类别:
Southeast Collaborative for Innovative and Equitable Solutions to Chronic Disease Disparities
东南合作以创新和公平的方式解决慢性病差异
- 批准号:
10657748 - 财政年份:2021
- 资助金额:
-- - 项目类别:
Southeast Collaborative for Innovative and Equitable Solutions to Chronic Disease Disparities
东南合作以创新和公平的方式解决慢性病差异
- 批准号:
10494158 - 财政年份:2021
- 资助金额:
-- - 项目类别:
Polygenic risk scores and health disparities: the role of blood cells immune response and evolutionary adaptation
多基因风险评分和健康差异:血细胞免疫反应和进化适应的作用
- 批准号:
10613573 - 财政年份:2021
- 资助金额:
-- - 项目类别:
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