ENIGMA Center for Worldwide Medicine, Imaging & Genomics
ENIGMA 全球医学影像中心
基本信息
- 批准号:8774373
- 负责人:
- 金额:$ 208.76万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2014
- 资助国家:美国
- 起止时间:2014-09-29 至 2018-09-30
- 项目状态:已结题
- 来源:
- 关键词:Acquired Immunodeficiency SyndromeAlgorithmsAttention deficit hyperactivity disorderAutistic DisorderBig DataBiological MarkersBipolar DisorderBrainBrain DiseasesBrain imagingClinicalCollaborationsCombinatoricsComplexComputational algorithmComputer softwareCountryDataData SetDiagnosisDiagnosticDiseaseDrug TargetingEducational workshopGenesGeneticGenomeGenomicsGoalsHIVHumanImageInstitutionInternetJointsLearningMachine LearningMajor Depressive DisorderMathematicsMedicineModalityModelingNational Human Genome Research InstituteNational Institute of Biomedical Imaging and BioengineeringNational Institute of Child Health and Human DevelopmentNational Institute of Drug AbuseNational Institute of Mental HealthNational Institute of Neurological Disorders and StrokeNational Institute on Alcohol Abuse and AlcoholismNatureObsessive-Compulsive DisorderPrognostic MarkerRecording of previous eventsResearchResearch InfrastructureSchizophreniaSchoolsScienceScientistTalentsTrainingTraining ProgramsUnited States National Institutes of HealthWorkaddictionbasechromosome 22q deletion syndromecomputer scienceinnovationmultidisciplinarymultitaskneuroimagingnovelnovel strategiesoutcome forecastpublic health relevancescreeningsuccesstoolworking group
项目摘要
DESCRIPTION (provided by applicant): The ENIGMA Center for Worldwide Medicine, Imaging and Genomics is an unprecedented global effort bringing together 287 scientists and all their vast biomedical datasets, to work on 9 major human brain diseases: schizophrenia, bipolar disorder, major depression, ADHD, OCD, autism, 22q deletion syndrome, HIV/AIDS and addictions. ENIGMA integrates images, genomes, connectomes and biomarkers on an unprecedented scale, with new kinds of computation for integration, clustering, and learning from complex biodata types. ENIGMA, founded in 2009, performed the largest brain imaging studies in history (N>26,000 subjects; Stein +207 authors, Nature Genetics, 2012) screening genomes and images at 125 institutions in 20 countries. Responding to the BD2K RFA, ENIGMA'S Working Groups target key programmatic goals of BD2K funders across the NIH, including NIMH, NIBIB, NICHD, NIA, NINDS, NIDA, NIAAA, NHGRI and FIC. ENIGMA creates novel computational algorithms and a new model for Consortium Science to revolutionize the way Big Data is handled, shared and optimized. We unleash the power of sparse machine learning, and high dimensional combinatorics, to cluster and inter-relate genomes, connectomes, and multimodal brain images to discover diagnostic and prognostic markers. The sheer computational power and unprecedented collaboration advances distributed computation on Big Data leveraging US and non-US infrastructure, talents and data. Our projects will better identify factors that resist and promote brain disease, that help diagnosis and prognosis, and identify new mechanisms and drug targets. Our Data Science Research Cores create new algorithms to handle Big Data from (1) Imaging Genomics, (2) Connectomics, and (3) Machine Learning & Clinical Prediction. Led by world leaders in the field who developed major software packages (e.g., Jieping Ye/SLEP), we prioritize trillions of computations for gene-image clustering, distributed multi-task machine learning, and new approaches to screen brain connections based on the Partition Problem in mathematics. Our ENIGMA Training Program offers a world class Summer School coordinated with other BD2K Centers, worldwide scientific exchanges. Challenge-based Workshops and hackathons to stimulate innovation, and Web Portals to disseminate tools and engage scientists in Big Data science.
描述(由申请人提供):ENIGMA全球医学、成像和基因组学中心是一个前所未有的全球努力,汇集了287名科学家和他们所有庞大的生物医学数据集,研究9种主要的人类脑部疾病:精神分裂症、双相情感障碍、重度抑郁症、多动症、强迫症、自闭症、22q缺失综合征、艾滋病毒/艾滋病和成瘾。ENIGMA以前所未有的规模整合了图像、基因组、连接体和生物标志物,并采用了新的计算方法来整合、聚类和从复杂的生物数据类型中学习。ENIGMA成立于2009年,在20个国家的125个机构中进行了历史上规模最大的脑成像研究(N bbb26,000名受试者;Stein +207名作者,Nature Genetics, 2012),筛选基因组和图像。作为对BD2K RFA的回应,ENIGMA的工作组针对NIH的BD2K资助者的关键项目目标,包括NIMH、NIBIB、NICHD、NIA、NINDS、NIDA、NIAAA、NHGRI和FIC。ENIGMA为Consortium Science创造了新颖的计算算法和新模型,彻底改变了大数据的处理、共享和优化方式。我们释放了稀疏机器学习和高维组合学的力量,以聚类和相互关联的基因组,连接体和多模态脑图像来发现诊断和预后标记。凭借强大的计算能力和前所未有的协作,利用美国和非美国的基础设施、人才和数据,推动了大数据分布式计算的发展。我们的项目将更好地识别抵抗和促进脑部疾病的因素,帮助诊断和预后,并确定新的机制和药物靶点。我们的数据科学研究核心创建了新的算法来处理来自(1)成像基因组学,(2)连接组学和(3)机器学习和临床预测的大数据。在该领域开发主要软件包的世界领导者(例如,叶杰平/SLEP)的带领下,我们优先考虑数万亿的基因图像聚类计算,分布式多任务机器学习以及基于数学分割问题筛选大脑连接的新方法。我们的ENIGMA培训计划提供了一个世界级的暑期学校,与其他BD2K中心协调,全球科学交流。以挑战为基础的研讨会和黑客马拉松,以刺激创新,以及门户网站,以传播工具并吸引科学家参与大数据科学。
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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PAUL M THOMPSON其他文献
PAUL M THOMPSON的其他文献
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{{ truncateString('PAUL M THOMPSON', 18)}}的其他基金
FiberNET: Deep learning to evaluate brain tract integrity worldwide and in AD
FiberNET:深度学习评估全球和 AD 脑道完整性
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10814696 - 财政年份:2020
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$ 208.76万 - 项目类别:
ENIGMA-SD: Understanding Sex Differences in Global Mental Health through ENIGMA
ENIGMA-SD:通过 ENIGMA 了解全球心理健康中的性别差异
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9892045 - 财政年份:2018
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$ 208.76万 - 项目类别:
Multi-Source Sparse Learning to Identify MCI and Predict Decline
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9008380 - 财政年份:2016
- 资助金额:
$ 208.76万 - 项目类别:
ENIGMA Center for Worldwide Medicine, Imaging & Genomics
ENIGMA 全球医学影像中心
- 批准号:
9108710 - 财政年份:2014
- 资助金额:
$ 208.76万 - 项目类别:
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