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e-Neuroscience: challenges and triumphs in integrating distributed data from molecules to brains

Abstract

Imaging, from magnetic resonance imaging (MRI) to localization of specific macromolecules by microscopies, has been one of the driving forces behind neuroinformatics efforts of the past decade. Many web-accessible resources have been created, ranging from simple data collections to highly structured databases. Although many challenges remain in adapting neuroscience to the new electronic forum envisioned by neuroinformatics proponents, these efforts have succeeded in formalizing the requirements for effective data sharing and data integration across multiple sources. In this perspective, we discuss the importance of spatial systems and ontologies for proper modeling of neuroscience data and their use in a large-scale data integration effort, the Biomedical Informatics Research Network (BIRN).

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Figure 1: A query result from the CCDB shows a dynamically generated view of the type of data available for any given dataset.
Figure 2: Portion of UMLS showing concepts related through the “child (is_a)” relationship shown using a graphical browsing tool developed by BIRN.
Figure 3: The Smart Atlas tool is being developed as a graphical interface and spatial query tool for distributed, spatially registered multi-scale imaging data in the Mouse BIRN.

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Acknowledgements

This work was supported by NIH grants from the National Center for Research Resources (RR04050, RR08605) and the Human Brain Project (DA016602), and funded by the National Institute on Drug Abuse, the National Institute of Biomedical Imaging and Bioengineering and the National Institute of Mental Health. Further funding was provided by NSF grants supporting the National Partnership for Advanced Computational Infrastructure (NSF-ASC 97-5249 and MCB-9728338). The BIRN is supported by NIH grants RR08605-08S1 (BIRN-CC) and RR043050-S2 (Mouse BIRN).

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Correspondence to Mark H Ellisman.

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Martone, M., Gupta, A. & Ellisman, M. e-Neuroscience: challenges and triumphs in integrating distributed data from molecules to brains. Nat Neurosci 7, 467–472 (2004). https://doi.org/10.1038/nn1229

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