SenseLab: Integration of Multidisciplinary Sensory Data

SenseLab：多学科感官数据整合

基本信息

批准号：
9302332
负责人：
MICHAEL L HINES
金额：
$ 66.5万
依托单位：
YALE UNIVERSITY
依托单位国家：
美国
项目类别：
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/9302332
关键词：
3-Dimensional Address Architecture Archives 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 Medical center Modeling Molecular Models Morphology Mus Nervous system structure Neurons Neurophysiology - biologic function Neurosciences Odors Olfactory Pathways Ontology Pattern Pattern Recognition Process Pythons Research Research Infrastructure Research Support Resources Role Sensory Signal Transduction Smell Perception Synapses System Testing Work base clinically relevant computational neuroscience computer cluster computer studies data integration data modeling design experimental study granule cell information framework innovation insight interoperability mitral cell molecular modeling multidisciplinary nervous system disorder neuroinformatics novel olfactory bulb olfactory receptor programs public health relevance relating to nervous system response simulation supercomputer tool

项目摘要

DESCRIPTION (provided by applicant): 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.

描述（由申请人提供）：SenseLab 的总体目标是通过创新的数据库和工具整合多学科神经科学数据，使用嗅觉系统作为可以推广到整个神经系统的模型。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从基因和蛋白质到神经元到电路等多个级别的实验数据和计算模型。 SenseLab 拥有三个基础：Perry Miller 指导的神经信息学、Gordon Shepherd 的实验数据以及 Michael Hines 的计算模型。其中一个重点是 ModelDB，它正在强劲增长，拥有 800 多个计算模型。我们将构建新功能，以便能够使用 ModelSearch 和 ModelView 等新工具来探索模型。我们将通过 Micro CircuitDB 支持新兴的脑微电路领域，该领域目前包含 200 多个模型。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 将为嗅觉受体数据库 (ORDB) 添加分子模型，以增强其当前包含的 14,000 多个化学感应基因和蛋白质的实用性。为了加强互操作，我们将继续与神经科学信息框架（NIF）和国际神经信息学协调设施（INCF）密切合作，开发神经元和微电路的通用本体。 Miller 博士及其耶鲁大学医学信息学中心同事的支持至关重要，这使 SenseLab 能够继续开发用于数据库构建和互操作的最先进的基础设施和工具。我们将探索设计、调整和/或增强各个 SenseLab 数据库的创新方法，以促进与其他神经科学数据库、工具和资源（例如 NIF）的稳健互操作。在我们的实验和计算研究中，我们将开发新一代大规模微电路模型，该模型真实地表示具有重叠树突域和分布式突触相互作用的多种神经元类型的详细 3 维形态。由 Hines 博士开发的 NEURON 模拟器的独特之处在于其在大规模并行集群计算机上计算该模型的能力。我们将使用与 Justus Verhagen 博士实验室持续合作的实验数据来测试该模型，并将与研究嗅球和其他系统的其他实验室共享该模型。总之，这种将实验数据集成到实际计算模拟中的多学科和多层次方法应该作为嗅觉处理分析和当前整个大脑数据集成尝试的模型。