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）：尽管神经系统含有惊人的神经元，但可以使用电生理，形态学和分子标记来对神经元进行分类。 分类可以变得足够具体，尤其是在无脊椎动物中，以鉴定单个神经元并绘制不同的神经回路。 对神经元和映射电路进行分类对于神经科学非常有价值，因为它阐明了神经系统的基本结构，为理解脑功能障碍提供了框架。 不幸的是，进步很慢，因为这项工作很乏味，没有标准的方式来代表，存储和分析这些努力中出现的神经元类型和接线图。 为了改善进步，该项目将开发神经元，这是一个公众的在线数据库及其突触连接，该数据库将作为重要的知识源和新型神经元类型的新颖信息来源和新颖的信息学工具。 通过神经科学家和计算机科学家之间的合作，将开发一个原型神经库，以支持对已识别神经元的丰富，灵活的描述，允许标记重要的识别功能，并提供源信息和可提取的登录编号。 为了促进进一步的电路映射，Neuronbank将有将新观察结果与已知细胞类型进行比较的设施，并建议确定细胞是否新颖的诊断。 Neuronbank还将具有创新的3D可视化系统，以直观地代表神经元位置。 该实现将允许其他研究人员轻松安装和修改其他神经元数据库，从而使数据库联合会的演变结合了广泛的数据集。 为了进行公路测试原型，Neuronbank将在Molluscs Tritonia Diomedea和Aplysia Californica中提供大量数据集，这都是用于运动模式，学习和记忆的重要模型系统。 然后，Neuronbank将被用作探索新神经元类型的这些系统的信息学工具。 该提案以多种方式实现了PAR-03-036（神经信息学研究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的影响，因为它实现了一种独特的神经信息学方法，用于神经元鉴定和神经回路分析。

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