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ShareFeb. 8, 2011 — Modern brain research generates immense quantities of data across different levels of detail, from gene activity to large-scale structure, using a wide array of methods. Each method has its own type of data and is stored in different databases. Integrating findings across levels of detail and from different databases, for example to find a link between gene expression and disease, is therefore challenging and time consuming. In addition, combining data from multiple types of brain studies provides a basis for new insights and is crucial for the progress of neuroscience research. Far too often, scientific progress is hindered by technical barriers to integrating data from different experiments and laboratories.
A major step in addressing these problems, a standard toolset that allows different types of neuroscience data to be combined and compared, is now available for one of the most important subjects in experimental neuroscience: the mouse, Mus musculus. A paper describing the vision and key steps that led to the creation of a digital mouse brain atlasing framework for sharing data appears in the online journal PLoS Computational Biology, published by the Public Library of Science.
In this landmark publication, the INCF Digital Atlasing Task Force announces a digital atlasing framework which consists of Waxholm Space (WHS; named in honor of the group's first meeting location) and a supporting web-based Digital Atlasing Infrastructure (DAI). Together they enable the integration of data from genetic, anatomical and functional imaging studies.
"By enabling researchers to link genetic studies with large-scale brain structure and behavior, we will catalyze both basic and medical neuroscience research -- precisely the reason INCF was founded in the first place." -- Dr. Sean Hill, Executive Director, INCF.
Three major online mouse brain resources -- the Allen Mouse Brain Atlas, the Edinburgh Mouse Atlas Project, and an effort from UCSD (primarily the Cell Centered Database) -- are now integrated with the INCF Digital Atlasing Infrastructure and therefore working together. This interoperability will facilitate future research as well as increase the value of previously acquired data.
WHS and DAI were developed with coordination, organization and funding from the International Neuroinformatics Coordinating Facility (INCF). They are a collaborative project, spanning more than two years, of the now retired INCF Standards in Digital Atlasing Task Force. Since then, new Task Forces have been formed to continue and expand on this work. A more detailed publication of this group's recommendations can be found in their report, published in September 2009 (see link below).
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The above story is reprinted from materials provided by INCF - International Neuroinformatics Coordinating Facility, via EurekAlert!, a service of AAAS.
Note: Materials may be edited for content and length. For further information, please contact the source cited above.
Journal References:
- Michael Hawrylycz, Richard A. Baldock, Albert Burger, Tsutomu Hashikawa, G. Allan Johnson, Maryann Martone, Lydia Ng, Chris Lau, Stephen D. Larsen, Jonathan Nissanov, Luis Puelles, Seth Ruffins, Fons Verbeek, Ilya Zaslavsky, Jyl Boline. Digital Atlasing and Standardization in the Mouse Brain. PLoS Computational Biology, 2011; 7 (2): e1001065 DOI: 10.1371/journal.pcbi.1001065
- Douglas M. Bowden, G. Allan Johnson, Laszlo Zaborsky, William D.K. Green, Eider Moore, Alexandra Badea, Mark F. Dubach, Fred L. Bookstein. A symmetrical Waxholm canonical mouse brain for NeuroMaps. Journal of Neuroscience Methods, 2011; 195 (2): 170 DOI: 10.1016/j.jneumeth.2010.11.028
- G. Allan Johnson, Alexandra Badea, Jeffrey Brandenburg, Gary Cofer, Boma Fubara, Song Liu, Jonathan Nissanov. Waxholm Space: An image-based reference for coordinating mouse brain research. NeuroImage, 2010; 53 (2): 365 DOI: 10.1016/j.neuroimage.2010.06.067
Note: If no author is given, the source is cited instead.
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