NeuroMorpho.Org Implementation of Digital Neuroscience: Dense Coverage and Integration with the NIF

被引:48
作者
Halavi, Maryam [1 ,2 ]
Polavaram, Sridevi [1 ,2 ]
Donohue, Duncan E. [1 ,2 ]
Hamilton, Gail [3 ]
Hoyt, Jeffrey [3 ]
Smith, Kenneth P. [3 ]
Ascoli, Giorgio A. [1 ,2 ]
机构
[1] George Mason Univ, Krasnow Inst Adv Study, Ctr Neural Informat Struct & Plast, Fairfax, VA 22030 USA
[2] George Mason Univ, Krasnow Inst Adv Study, Mol Neurosci Dept, Fairfax, VA 22030 USA
[3] Mitre Corp, Mclean, VA USA
基金
美国国家卫生研究院;
关键词
Neuronal morphology; Digital reconstruction; Data sharing; Neuroscience information framework; Axonal arbors; Dendritic trees;
D O I
10.1007/s12021-008-9030-1
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
Neuronal morphology affects network connectivity, plasticity, and information processing. Uncovering the design principles and functional consequences of dendritic and axonal shape necessitates quantitative analysis and computational modeling of detailed experimental data. Digital reconstructions provide the required neuromorphological descriptions in a parsimonious, comprehensive, and reliable numerical format. NeuroMorpho.Org is the largest web-accessible repository service for digitally reconstructed neurons and one of the integrated resources in the Neuroscience Information Framework (NIF). Here we describe the NeuroMorpho.Org approach as an exemplary experience in designing, creating, populating, and curating a neuroscience digital resource. The simple three-tier architecture of NeuroMorpho.Org (web client, web server, and relational database) encompasses all necessary elements to support a large-scale, integrate-able repository. The data content, while heterogeneous in scientific scope and experimental origin, is unified in format and presentation by an in house standardization protocol. The server application (MRALD) is secure, customizable, and developer-friendly. Centralized processing and expert annotation yields a comprehensive set of metadata that enriches and complements the raw data. The thoroughly tested interface design allows for optimal and effective data search and retrieval. Availability of data in both original and standardized formats ensures compatibility with existing resources and fosters further tool development. Other key functions enable extensive exploration and discovery, including 3D and interactive visualization of branching, frequently measured morphometrics, and reciprocal links to the original PubMed publications. The integration of NeuroMorpho.Org with version-1 of the NIF (NIFv1) provides the opportunity to access morphological data in the context of other relevant resources and diverse subdomains of neuroscience, opening exciting new possibilities in data mining and knowledge discovery. The outcome of such coordination is the rapid and powerful advancement of neuroscience research at both the conceptual and technological level.
引用
收藏
页码:241 / 252
页数:12
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