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Senselab databases integrate neuronal data and modeling.

Nicholas T. Carnevale1, Kei-Hoi Cheung2, Chiquito J. Crasto3, Michael L. Hines1, Luis Marenco2, Robert A. McDougal1*, Michele Migliore1, 4, Perry L. Miller2, Thomas M. Morse1, Samuel A. Neymotin1, Gordon M. Shepherd1, Rixin Wang2 and Yuguo Yu1, 5
  • 1 Yale University, Neurobiology, United States
  • 2 Yale University School of Medicine, Center for Medical Informatics, United States
  • 3 University of Alabama, Birmingham, Genetics, United States
  • 4 National Research Council, Institute of Biophysics, Italy
  • 5 Fudan University, Center for Computational Systems Biology, China

Since 1993, SenseLab has developed a suite of databases using the olfactory system as a model to enable the integration of neuroscience data in molecular biology, cell morphology, electrophysiology, and computational neuroscience. Our open-ended and flexible Entity Attribute Value with Classes and Relationships (EAV/CR) meta-schema facilitate the inclusion of data from multiple spatial scales and diverse areas by making it easy to continue to modify the schema to include new topics as necessary as the databases become populated and adopted more widely.
The current databases include CellPropDB, an archive for neuronal properties such as ion channels and receptors for particular neurons; NeuronDB archives these properties with respect to their spatial distribution in neuronal compartments; ModelDB is a repository of computational neuroscience computer code; MicrocircuitDB is a collection of computer code specific to circuits within brain regions; ORDB archives over 14,000 olfactory receptors; OdorDB archives over 200 odors that interact with ORs, OdorMapDB is an archive of olfactory bulb maps generated by different methods; and BrainPharm aims to archive drug and receptor interactions.
Recent developments in ModelDB include developing new search tools for making it easier for modelers to find models of interest. We recently provided a novel search tool, ModelSearch, available from the ModelDB home page, which combines free text and database pre-defined keyword searches into unique results sorted on model names. In collaboration with Channelpedia, we are developing methods to simplify searching for model components such as ion channels that are sometimes duplicated across different models. To make ModelDB models more easily interpreted, we are developing an HTML5 graphical model viewer (suppl. figure) based on NEURON's Model View tool. This view, accessible by a link from a supported model’s page, displays a 3d image of the neuron. The user may select specific ion channel mechanisms or synapses to view their runtime parameters and their distribution across the cell.
We have just created a new SenseLab database NeurosciDataDB for a collaboration to allow more transparent access to microcircuits and other data generated in electrophysiologial experiments. All data will be cross-linked with models, using a set of "tags". Clicking on a tag, for example "motor cortex", will bring up a list of both the models and the experimental data that is thus tagged.

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Acknowledgements

SenseLab is supported by NIDCD. We thank Brad Armstrong, Kyle Jensen, and Harold Prentiss for their contributions to the ModelView interface.

Keywords: Molecular Biology, cell morphology, Electrophysiology, Computational models, visualization

Conference: Neuroinformatics 2013, Stockholm, Sweden, 27 Aug - 29 Aug, 2013.

Presentation Type: Poster

Topic: General neuroinformatics

Citation: Carnevale NT, Cheung K, Crasto CJ, Hines ML, Marenco L, McDougal RA, Migliore M, Miller PL, Morse TM, Neymotin SA, Shepherd GM, Wang R and Yu Y (2013). Senselab databases integrate neuronal data and modeling.. Front. Neuroinform. Conference Abstract: Neuroinformatics 2013. doi: 10.3389/conf.fninf.2013.09.00079

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Received: 08 Apr 2013; Published Online: 11 Jul 2013.

* Correspondence: Dr. Robert A McDougal, Yale University, Neurobiology, New Haven, CT, 06520-8001, United States, robert.mcdougal@yale.edu