Computational resources and systems biological analyses of deep sequencing data for improved

深度测序数据的计算资源和系统生物学分析，以改进

• 批准号: 9910459
• 负责人: Dennis Paul Wall
• 金额: $ 14.75万
• 依托单位: HARVARD MEDICAL SCHOOL
• 依托单位国家: 美国
• 资助国家: 美国
• 起止时间: 至
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/9910459
• 关键词: Algorithm Design; Animal Model; Animals; Automobile Driving; Behavior; Bioinformatics; Biological; Computer Analysis; Data; Databases; Deposition; Drosophila genus; Elements; Generations; Genes; Goals; Homing; Informatics; Memory; Messenger RNA; Methods; MicroRNAs; Molecular; Phase; Phenotype; Regulation; Research Design; Retrieval; Running; Sleep; Synaptic plasticity; Systems Biology; Testing; Transcript; Transgenic Organisms; Work; behavioral plasticity; biological systems; classical conditioning; computing resources; deep sequencing; design; differential expression; exhaustion; experimental study; follow-up; improved; informatics infrastructure; innovation; mRNA Expression; mutant; neural circuit; neuromuscular system; novel; programs; screening; sensor; tool; transcriptome; transcriptome sequencing

Core C Project Leader: Wall, Dennis P. Project Summary / Abstract The study of miRs and their regulatory control has led to impressive bioinformatic innovations with respect to algorithm design, target prediction, evolutionary canalization and divergence, and much more. What has not happened and is unique to this plan is the combination of these informatics advances with comprehensive and integrated functional analysis in the intact animal. Core C, through its interactions with Core B and the three driving biological projects targeting regulatory influence of miRs on sleep, associative learning and memory, and the neuromuscular system will provide this innovation in a model organism where neural circuits can be analyzed at many levels from behavior to cellular and molecular details. Specifically, Core C will develop the informatics infrastructure necessary to store and analyze all experimental data coming from these 4 sectors of the center proposal and, through reciprocal design, enable fast characterization of the functional impacts of specific miRs to study the impact on target networks and to determine instances of functional convergence. Core C will deliver the tools necessary for each driving project to form hypotheses about the influence of specific miRs on gene networks through microRNA recognition elements (MREs) in target mRNAs, and help steer the design of new experiments that have the highest likelihood of revealing the mechanisms of regulatory control that impact phenotype.

核心C项目负责人：Wall，Dennis P. 项目总结/摘要 miR及其调控的研究已经导致了令人印象深刻的生物信息学创新， 算法设计、目标预测、进化渠化和发散等等。哪些没有 这一计划的独特之处在于将这些信息学进步与全面的 完整动物的综合功能分析。核心C，通过与核心B和三个 推动生物学项目，目标是miR对睡眠、联想学习和记忆的调节影响， 神经肌肉系统将在生物模型中提供这种创新， 从行为到细胞和分子细节的多个层面进行分析。具体来说，核心C将开发 信息学基础设施必要的存储和分析所有实验数据来自这4个部门， 该中心的建议，并通过互惠设计，使快速表征的功能影响， 具体的miR，以研究对目标网络的影响，并确定功能融合的情况。 核心C将为每个驱动项目提供必要的工具，以形成关于以下因素影响的假设： 通过靶mRNA中的microRNA识别元件（MRE）在基因网络上的特异性miR， 指导新实验的设计，这些实验最有可能揭示调控机制， 控制影响表型。