Data Management and Analysis Core

数据管理与分析核心

• 批准号: 10698068
• 负责人: BOOIL JO
• 金额: $ 14.47万
• 依托单位: STANFORD UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-09-06 至 2027-08-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10698068
• 关键词: Age; Animal Genetics; Animal Model; Behavior; Behavioral; Behavioral Symptoms; Biological; Calibration; Chick; Clinical; Cognition; Cognitive; Collection; Comparative Biology; Data; Data Analyses; Data Analytics; Data Set; Development; Diphenhydramine; Disease model; Double-Blind Method; Electroencephalography; Electrophysiology (science); Ensure; Experimental Animal Model; Gender; Genetic Diseases; Genetic Models; Heterogeneity; Human; Impairment; Leadership; Maintenance; Measures; Modeling; Mus; Neurobehavioral Manifestations; Noise; Participant; Pharmaceutical Preparations; Phenotype; Placebo Control; Polysomnography; Quality Control; Randomized; Reproducibility; Research Personnel; Rest; Role; Secure; Sleep; Sleep Architecture; Sleep Fragmentations; Source; Statistical Data Interpretation; Statistical Methods; Structure; Symptoms; System; Validation; Variant; Zebrafish; actigraphy; adolescent with autism spectrum disorder; aged; autism spectrum disorder; autistic children; awake; circadian; cognitive function; comparative; data integration; data management; data visualization; design; improved; mouse model; multimodal data; multimodality; programs; repetitive behavior; response; sleep physiology; social communication; zolpidem

ABSTRACT: DATA MANAGEMENT AND ANALYTIC CORE (DMAC) In our proposed ACE, we propose a multi-modal, cross-species program which encompasses four synergistic projects aimed at characterizing the role of sleep fragmentation and sleep physiology on the core symptoms, repetitive behaviors and cognitive function in Autism Spectrum Disorder (ASD). Leveraging comparative biology across humans with ASD and complementary genetic animal models of ASD, the overall aims of our ACE are to examine if multisystem sleep measurements across species a) converge on a common phenotype of sleep fragmentation and architecture in ASD; b) are differentially associated with the core, behavioral and cognitive symptoms of ASD; and c) if sleep normalization in humans with ASD and animal models of ASD, alleviate the core, behavioral and cognitive symptoms of ASD. The management and analysis of such large, multi-domain, comparative data sets include careful maintenance and tracking of the quality and eventual sources of heterogeneity, correct calibration and quality control of the data and control for the multiplicity of choices in the normalization and metrics. The DMAC will employ a reproducible approach to the development of the complete statistical analyses and record to attain the following objectives. Objective 1: Coordination, transfer, integration and management of data across all ACE Projects, and their different platforms; Objective 2: Integration, calibration and normalization of data sets from the different sources; Objective 3: Design, Analysis, and Power Estimation; and Objective 4: Integrating and analyzing comparative data across the RAC and Projects 1-4.

摘要：数据管理与分析核心（dmac）