Virtual Fly Brain - a data hub for Drosophila neurobiology
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1
University of Cambridge, UK
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2
Edinburgh University, United Kingdom
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3
MRC Laboratory of Molecular Biology, United Kingdom
Drosophila neurobiology is on the cusp of a data explosion that could facilitate significant advances in our understanding of basic neurobiology. Realizing this promise will require intuitive tools that allow queries across diverse data types from multiple sources, including the literature. Virtual Fly Brain (VFB) [1] already partially fulfills this role, integrating neuroanatomical data from the literature with genomic and genetic data in the FlyBase genetic database. We are beginning to integrate bulk data, including large sets of annotated 3D images. Â An extensive ontology of Drosophila neuroanatomy provides the glue for data integration and the substrate for queries on VFB. This ontology is used by FlyBase to annotate expression and phenotype via a simple tagging model, but it also allows more sophisticated forms of data integration. The ontology uses the W3C standard ontology language OWL2 and a set of general relations for representing neuroanatomy [2], developed in coordination with the INCF funded Project for Ontologies in Neuroscience. The basic spatial reasoning that these relations allow is vital to VFB. It drives our queries of brain regions for innervating neurons, expression patterns and phenotypes and will soon drive our queries of annotated neuron images. Where individual annotated neurons can be mapped to known neuron classes, we can use information about the mapped class to enrich image queries. Conversely, we can use information extracted from neuron images about the location of neuron parts to enrich queryable information about mapped neuron classes. Our ontology also includes extensive use of relations for recording lineage, neurotransmitter and function and synaptic connections. The VFB query system will soon be extended to encompass these. Â We work with data providers to annotate images in a form that we can easily integrate. Where this is not possible, we analyse bulk image data using a pipeline that registers images to a standard, extracts spatial information and clusters neurons by shape. Where clustering predicts new isomorphic neuron classes, we incorporate these into our ontology. Â As well as providing a data integration hub for Drosophila neurobiology, our system has great potential for generalisation to other systems in neurobiology. [1] http://www.virtualflybrain.org ; Milyaev et al., 2012 http://dx.doi.org/10.1093/bioinformatics/btr677 [2] Osumi-Sutherland et al., 2012 http://dx.doi.org/10.1093/bioinformatics/bts113
Keywords:
digital atlasing
Conference:
5th INCF Congress of Neuroinformatics, Munich, Germany, 10 Sep - 12 Sep, 2012.
Presentation Type:
Demo
Topic:
Neuroinformatics
Citation:
Osumi-Sutherland
D,
Milyaev
N,
Costa
M,
Jefferis
G,
O'Kane
C and
Armstrong
J
(2013). Virtual Fly Brain - a data hub for Drosophila neurobiology.
Front. Neuroinform.
Conference Abstract:
5th INCF Congress of Neuroinformatics.
doi: 10.3389/conf.fninf.2013.08.00006
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Received:
21 Mar 2013;
Published Online:
27 Nov 2013.
*
Correspondence:
Dr. David Osumi-Sutherland, University of Cambridge, Cambridge, UK, djs93@gen.cam.ac.uk