NeuronBank: A Database for Identified Neurons and Synaptic Connections

NeuronBank：已识别神经元和突触连接的数据库

• 批准号: 7230058
• 负责人: Paul S Katz
• 金额: $ 12.72万
• 依托单位: GEORGIA STATE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2006
• 资助国家: 美国
• 起止时间: 2006-03-15 至 2009-02-28
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7230058
• 关键词: 3-Dimensional; Abdomen; Accession Number; Algorithms; Aplysia; Area; Beds; Behavior; Biological Markers; Biological Models; Biology; Brain; Cataloging; Catalogs; Cells; Classification; Collaborations; Communities; Complex; Computer software; Computers; Data; Data Set; Databases; Development; Diagnostic; Disease; Elements; Ensure; Evolution; Feedback; Functional disorder; Future; Ganglia; Generations; Goals; Imagery; Individual; Informatics; Institutes; Internet; Invertebrates; Knowledge; Lead; Learning; Location; Maps; Memory; Mining; Modeling; Motor; Myxoid cyst; Nervous system structure; Neurons; Neurosciences; Neurosciences Research; Numbers; Online Systems; Ontology; Pattern; Publishing; Purpose; Research; Research Personnel; Resources; Scientist; Services; Source; Speed; Standards of Weights and Measures; Structure; Synapses; System; Technology; Technology Development Study; Testing; Time; USA Georgia; Universities; Western Asia Georgia; Work; brain behavior; cell type; college; computer science; concept; data mining; database design; design; improved; innovation; interoperability; knowledge base; neural circuit; neuroinformatics; neuronal circuitry; novel; open source; programs; prototype; relating to nervous system; scale up; synergism; tool; web based interface

DESCRIPTION (provided by applicant): Although nervous systems contain staggering numbers of neurons, it is possible to use electrophysiological, morphological, and molecular markers to classify neurons. Classification can become specific enough, especially in invertebrates, to identify individual neurons and map distinct neural circuits. Classifying neurons and mapping circuits is extremely valuable for neuroscience, as it elucidates the fundamental structure of the nervous system, providing a framework for understanding brain dysfunction. Unfortunately, progress is slow, as the work is tedious and there is no standard way to represent, store, and analyze the neuron types and wiring diagrams that emerge from these efforts. To help improve progress this project will develop NeuronBank, a public, on-line database of identified neurons and their synaptic connections that will serve as an important knowledge source and a novel informatics tool for the identification of new neuron types. Through collaboration between neuroscientists and computer scientists, a prototype NeuronBank will be developed that supports rich, flexible descriptions of identified neurons, allows features important to identification to be flagged, and provides source information and citable accession numbers. To facilitate further circuit mapping, NeuronBank will have facilities for comparing new observations to known cell types and suggesting diagnostics for determining if the cell is novel. NeuronBank will also feature an innovative 3-D visualization system to intuitively represent neuron location. The implementation will allow additional NeuronBank databases to be installed and modified easily by other researchers, enabling the evolution of a federation of databases uniting broad data sets. To road- test the prototype, NeuronBank will be stocked with large data sets from the molluscs Tritonia diomedea and Aplysia californica, both important model systems for motor pattern generation, learning, and memory. NeuronBank will then be used as an informatics tool to explore these systems for new neuron types. This proposal serves the purposes of PAR-03-036 (Innovative exploratory studies and technology development in Neuroinformatics Research) in several ways. It develops a new database and tools for neuroinformatics research. It is likely to have a high impact on future neuroscience research as it implements a unique neuroinformatics approach to neuron identification and neural circuit analysis.

描述（由申请人提供）：虽然神经系统包含数量惊人的神经元，但可以使用电生理学、形态学和分子标记物对神经元进行分类。 分类可以变得足够具体，特别是在无脊椎动物中，以识别单个神经元并映射不同的神经回路。 神经元分类和映射电路对神经科学来说非常有价值，因为它阐明了神经系统的基本结构，为理解大脑功能障碍提供了一个框架。 不幸的是，进展缓慢，因为工作是乏味的，没有标准的方法来表示，存储和分析这些努力中出现的神经元类型和接线图。 为了帮助提高进展，该项目将开发NeuronBank，这是一个已识别神经元及其突触连接的公共在线数据库，将作为重要的知识来源和识别新神经元类型的新型信息学工具。 通过神经科学家和计算机科学家之间的合作，将开发一个原型NeuronBank，支持对已识别神经元的丰富、灵活的描述，允许标记对识别重要的特征，并提供源信息和可引用的登录号。 为了促进进一步的电路映射，NeuronBank将有设施将新的观察结果与已知的细胞类型进行比较，并提出诊断方法，以确定细胞是否是新的。 NeuronBank还将采用创新的3D可视化系统，直观地表示神经元的位置。 该实施将允许其他研究人员轻松安装和修改额外的NeuronBank数据库，从而实现数据库联盟的发展，将广泛的数据集统一起来。 为了对原型进行道路测试，神经银行将储备来自软体动物Tritonia diomedea和Aaprisia californica的大型数据集，这两种都是运动模式生成，学习和记忆的重要模型系统。 然后，NeuronBank将被用作信息学工具，以探索这些系统中的新神经元类型。 该提案以多种方式服务于PAR-03-036（神经信息学研究中的创新探索性研究和技术开发）的目的。 它为神经信息学研究开发了一个新的数据库和工具。 它可能会对未来的神经科学研究产生很大影响，因为它实现了一种独特的神经信息学方法来识别神经元和神经回路分析。

项目成果

NeuronBank: A Tool for Cataloging Neuronal Circuitry.

• DOI: 10.3389/fnsys.2010.00009
• 发表时间: 2010
• 期刊: Frontiers in systems neuroscience
• 影响因子: 3
• 作者: Katz PS;Calin-Jageman R;Dhawan A;Frederick C;Guo S;Dissanayaka R;Hiremath N;Ma W;Shen X;Wang HC;Yang H;Prasad S;Sunderraman R;Zhu Y
• 通讯作者: Zhu Y