SenseLab: Integration of Multidisciplinary Sensory Data

SenseLab：多学科感官数据整合

• 批准号: 8697553
• 负责人: MICHAEL L HINES
• 金额: $ 70.18万
• 依托单位: YALE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-08-01 至 2019-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8697553
• 关键词: 3-Dimensional; Address; Architecture; Archives; Base of the Brain; Biological Models; Brain; Brain Diseases; Brain region; Cells; Collaborations; Communities; Computer Simulation; Data; Databases; Development; Environment; Foundations; Functional disorder; Funding; Gene Proteins; Generations; Goals; Growth; Image; Individual; Informatics; International; Internet; Laboratories; Lead; Medical Informatics; Modeling; Molecular Models; Morphology; Mus; Nervous system structure; Neurons; Neurophysiology - biologic function; Neurosciences; Odors; Ontology; Pattern; Pattern Recognition; Process; Program Development; Pythons; Research; Research Infrastructure; Research Support; Resources; Role; Sensory; Smell Perception; Solutions; Synapses; System; Testing; Time; Work; base; clinically relevant; computer cluster; computer studies; data integration; data modeling; design; granule cell; information framework; innovation; insight; interoperability; molecular modeling; multidisciplinary; nervous system disorder; neuroinformatics; novel; olfactory bulb; olfactory receptor; programs; public health relevance; relating to nervous system; research study; response; signal processing; simulation; supercomputer; tool

SenseLab Renewal Summary The overall aim of SenseLab is to integrate multidisciplinary neuroscience data by means of innovative databases and tools, using the olfactory system as a model which can generalize across the nervous system. For this purpose we have created 8 interoperable databases that serve growing user communities for experimental data and computational models at multiple levels, from genes and proteins through neurons to circuits. SenseLab has three foundations: neuroinformatics directed by Perry Miller, experimental data by Gordon Shepherd, and computational modeling by Michael Hines. One focus will be on ModelDB, which is growing strongly with over 800 computational models. We will build new functionality to enable the models to be explored with new tools including ModelSearch and ModelView. We will support an emerging field of brain microcircuits through MicrocircuitDB, which currently contains over 200 models. A new BrainPathPhysiolDB will contain over 100 models of neuron pathophysiology with clinical relevance. A new ORModelDB will add molecular models to the Olfactory Receptor Database (ORDB) to enhance the utility of the 14,000+ chemosensory genes and proteins that it currently contains. To enhance interoperation we will continue to work closely with the Neuroscience Information Framework (NIF) and the International Neuroinformatics Coordination Facility (INCF) to develop a general ontology for neurons and microcircuits. Support by Dr. Miller and his colleagues in the Yale Center for Medical Informatics will be critical, and enable SenseLab to continue developing its state-of-the-art infrastructure and tools for database construction and interoperation. We will explore innovative ways in which individual SenseLab databases can be designed, adapted, and/or enhanced to facilitate robust interoperation with other neuroscience databases, tools, and resources such as the NIF. In our experimental and computational studies we will develop a new generation of large-scale microcircuit models which realistically represent the detailed 3 dimensional morphology of multiple neuron types with overlapping dendritic fields and distributed synaptic interactions. The NEURON simulator, developed by Dr. Hines, is unique in its capability for computing this model on massively parallel cluster computers. We will test the model with experimental data from an ongoing collaboration with the lab of Dr. Justus Verhagen, and will share the model with other labs working on the olfactory bulb and other systems. In summary, this multidisciplinary and multilevel approach using integration of experimental data into realistic computational simulations should serve as a model for analysis of olfactory processing and for current attempts at data integration throughout the brain.

SenseLab更新 总结 SenseLab的总体目标是通过创新的方法整合多学科神经科学数据。 数据库和工具，使用嗅觉系统作为模型，可以概括整个神经系统。 为此，我们创建了8个可互操作的数据库，为不断增长的用户社区提供服务， 从基因和蛋白质到神经元， 电路. SenseLab有三个基础：佩里米勒指导的神经信息学， Gordon Shepherd和Michael Hines的计算建模。其中一个重点是ModelDB， 随着超过800个计算模型的发展而强劲增长。我们将构建新的功能，使模型能够 可以使用新工具进行探索，包括ModelSearch和ModelView。 我们将支持一个新兴的大脑领域 MicrocircuitDB中的微电路，目前包含200多个模型。一个新的BrainPathPhysiolDB 将包含100多个具有临床相关性的神经元病理生理学模型。 新的ORModelDB将添加 嗅觉受体数据库（ORDB）的分子模型，以提高14，000 + 化学感受基因和蛋白质。为了加强互操作性，我们将继续 与神经科学信息框架（NIF）和国际神经信息学密切合作 协调设施（INCF）开发神经元和微电路的通用本体。 由米勒博士提供支持 和他在耶鲁大学医学信息学中心的同事们将是至关重要的，并使SenseLab能够继续 为数据库建设和互操作开发其最先进的基础设施和工具。我们将 探索创新方法，设计、调整和/或增强单个SenseLab数据库 促进与其他神经科学数据库、工具和资源（如NIF）的强大互操作。在 我们的实验和计算研究，我们将开发新一代的大规模微电路 模型真实地表示多种神经元类型的详细三维形态， 重叠的树突区域和分布的突触相互作用。神经元模拟器，由博士开发。 Hines，是独特的，在其大规模并行集群计算机上计算这个模型的能力。 我们将测试 该模型的实验数据来自正在进行的合作与博士贾斯特斯Verdegli的实验室，并将 与其他研究嗅球和其他系统的实验室分享这个模型。 总之，这 多学科和多层次的方法，使用实验数据集成到现实的计算 模拟应该作为分析嗅觉处理和当前数据尝试的模型 整合到整个大脑中。