NeuroML-DB: Sharing and characterizing data-driven neuroscience models described in NeuroML.
NeuroML-DB: Sharing and characterizing data-driven neuroscience models described in NeuroML.
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DOI：
10.1371/journal.pcbi.1010941
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发表时间：
2023-03
影响因子：
4.3
通讯作者：
中科院分区：
文献类型：
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作者：
随着研究人员开发越来越复杂和规模的神经系统计算模型，通常情况下，完全从头模型开发是不切实际和低效的。因此，迫切需要快速找到，评估，重用，并建立在其他研究人员开发的模型和模型组件。我们介绍了NeuroML数据库（NeuroML-DB.org），该数据库是为满足这一需求而开发的，并补充了其他模型共享资源。NeuroML-DB存储了1,500多个先前发布的离子通道、细胞和网络模型，这些模型已经被翻译成模块化NeuroML模型描述语言。该数据库还提供了与其他神经科学模型数据库（ModelDB，Open Source Brain）的相互链接，以及对原始模型出版物（PubMed）的访问。这些链接沿着神经科学信息框架（NIF）搜索功能提供了与其他神经科学社区建模资源的深度集成，并极大地促进了寻找合适模型以供重用的任务。作为一种中间语言，NeuroML及其工具生态系统可以将模型有效地转换为其他流行的模拟器格式。模块化的特性还可以有效分析大量模型并检查其属性。数据库的搜索功能，以及基于网络的，可编程的在线界面，使社区的研究人员能够快速评估存储的模型电生理学，形态学和计算复杂性的属性。我们使用这些功能来执行神经元和离子通道模型的数据库规模的分析，并描述了一种新的四面体结构的模型属性和功能的空间中的细胞模型集群形成。该分析提供了关于模型相似性的进一步信息，以丰富数据库搜索。神经元及其电路的计算模型越来越多地被神经科学研究人员用作探索大脑功能基本方面的工具。在这里，我们描述了神经元和网络的计算模型的数据库，使其更容易评估和重用这些模型。数据库中的模型以标准格式提供，称为NeuroML，这使得使用广泛的仿真软件平台在仿真研究中扩展和重用模型变得更加容易。使用这种标准格式还可以更轻松地以自动化的方式表征模型，并分析来自模型模拟的模拟数据特征之间的关系。
As researchers develop computational models of neural systems with increasing sophistication and scale, it is often the case that fully de novo model development is impractical and inefficient. Thus arises a critical need to quickly find, evaluate, re-use, and build upon models and model components developed by other researchers. We introduce the NeuroML Database (NeuroML-DB.org), which has been developed to address this need and to complement other model sharing resources. NeuroML-DB stores over 1,500 previously published models of ion channels, cells, and networks that have been translated to the modular NeuroML model description language. The database also provides reciprocal links to other neuroscience model databases (ModelDB, Open Source Brain) as well as access to the original model publications (PubMed). These links along with Neuroscience Information Framework (NIF) search functionality provide deep integration with other neuroscience community modeling resources and greatly facilitate the task of finding suitable models for reuse. Serving as an intermediate language, NeuroML and its tooling ecosystem enable efficient translation of models to other popular simulator formats. The modular nature also enables efficient analysis of a large number of models and inspection of their properties. Search capabilities of the database, together with web-based, programmable online interfaces, allow the community of researchers to rapidly assess stored model electrophysiology, morphology, and computational complexity properties. We use these capabilities to perform a database-scale analysis of neuron and ion channel models and describe a novel tetrahedral structure formed by cell model clusters in the space of model properties and features. This analysis provides further information about model similarity to enrich database search. Computational models of neurons and their circuits are increasingly used by neuroscience researchers as a tool to probe fundamental aspects of brain function. Here we describe a database of computational models of neurons and networks that makes it easier to evaluate and reuse these models. The models in the database are available in a standard format, called NeuroML, that makes it easier to extend and reuse the models in simulation studies using a wide range of simulation software platforms. The use of this standard format also makes it easier to characterize models in an automated way and analyze relationships across the features of simulated data from model simulations.
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影响因子：
3.7
作者：
Druckmann, Shaul;Hill, Sean;Segev, Idan
通讯作者：
Segev, Idan
DOI：
10.1098/rstb.2017.0380
发表时间：
2018-09-10
期刊：
Philosophical transactions of the Royal Society of London. Series B, Biological sciences
影响因子：
--
作者：
Cantarelli M;Marin B;Quintana A;Earnshaw M;Court R;Gleeson P;Dura-Bernal S;Silver RA;Idili G
通讯作者：
Idili G
影响因子：
7.7
作者：
Bezaire, Marianne J.;Raikov, Ivan;Soltesz, Ivan
通讯作者：
Soltesz, Ivan
影响因子：
34.7
作者：
Ascoli, Giorgio A.;Alonso-Nanclares, Lidia;Anderson, Stewart A.;Barrionuevo, German;Benavides-Piccione, Ruth;Burkhalter, Andreas;Buzsaki, Gyoergy;Cauli, Bruno;DeFelipe, Javier;Fairen, Alfonso;Feldmeyer, Dirk;Fishell, Gord;Fregnac, Yves;Freund, Tamas F.;Gardner, Daniel;Gardner, Esther P.;Goldberg, Jesse H.;Helmstaedter, Moritz;Hestrin, Shaul;Karube, Fuyuki;Kisvarday, Zoltan F.;Lambolez, Bertrand;Lewis, David A.;Marin, Oscar;Markram, Henry;Munoz, Alberto;Packer, Adam;Petersen, Carl C. H.;Rockland, Kathleen S.;Rossier, Jean;Rudy, Bernardo;Somogyi, Peter;Staiger, Jochen F.;Tamas, Gabor;Thomson, Alex M.;Toledo-Rodriguez, Maria;Wang, Yun;West, David C.;Yuste, Rafael
通讯作者：
Yuste, Rafael
影响因子：
1.6
作者：
Boyle, Jordan H.;Cohen, Netta
通讯作者：
Cohen, Netta