WikiNeuron: Semantic Neuro-Mashup

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Presentation transcript:

WikiNeuron: Semantic Neuro-Mashup http://neuroweb3.med.yale.edu/mediawiki/index.php/WikiNeuron Kei Cheung Yale Center for Medical Informatics

Introduction There has been an increasing number of Bio-Wiki projects including Gene Wiki, Wikiproteins, Wikipathways, Proteopedia, SNPedia, etc Why not creating a collaborative and semantic-enabled Wiki for the neuroscience domain If we have “calling on million minds for community annotation in Wikiproteins”, why not “calling on trillion neurons for community annotation in WikiNeuron”

WikiNeuron Protoype It is conceived as collaborative knowledge acquisition, annotation, and integration for neurosciences It is implemented using Semantic MediaWiki (SMW), which is a semantic extension of MediaWiki that drives large-scale community projects like Wikipedia This prototype is developed by SenseLab in collaboration with NIF (Neuroscience Information Framework)

Overview of SMW It is page-centric. There are different types of pages: Categories: support of hierarchical structure E.g., Person is a category, Scientist can be a subcategory of Peron Articles: they are category instances/members E.g., The home page of Jone Smith is a page of the Category Person Properties: attributes that are used to annotate page contents and relate pages E.g., Address, Age, Sex, Email, and Friends are properties of Jone Smith

Overview of SMW It provides an internal semantic query language It supports SPARQL endpoint It supports Open Linked Data through a utility that allows RDF data export It has extensions such as the Halo extension that allows incorporation of ontologies into semantic annotation of wiki content.

WikiNeuron Semantic Structure Categories: Brain, Database, Literature These categories and their subcategories describe databases, literature, brain functions, and brain structure (at different levels of granularity). In addition to these categories, properties are defined to annotate data/literature and integrate them with brain functions/structure. Many of WikiNeuron’s categories/properties come from the NIF ontology

Brain Category Trees Brain Brain Region Neuron Cerebellum, Hippocampus, Neocortex, … Neuron Principal neuron CA1 Pyramidal Neuron, Cerebellar Purkinje Neuron, … Interneuron Cerebellar Granule Cell Neuronal Properties (Synapses) Receptor GABA-A receptor, … Transmitter Dopamine, … Current IA, …

Other Categories Database Scientific literature Person Neurocience Database, … Scientific literature PubMed Articles, … Person Contributors, administrators, …

Semantic Trees of the Mind Category page Brain functions Brain regions Neurons synapses Data/paper page Property connecting Data/paper pages Property connecting Category pages See next slide The diagram below shows the apical tufts of 2 cortical layer V pyramidal cells filled with biocytin and stained with a Texas red / avidin-D conjugate, then counterstained with a green fluorescent nissl stain. Neuroantonomy/Neurophysiology Forest (other forests can exist)

Automatic Generation and Import of Data/Literature Pages paper Multimedia data Triplestore Relational database Mapping between the source data structure and the target semantic Wiki page structure (wiki template may facitilate this mapping

Demo http://neuroweb3.med.yale.edu/mediawiki/index.php/WikiNeuron

Database and Literature

NIF Database Entry

Literature

Semantic Markup

Future Directions Use WikiNeuron to drive some of the BioRDF activities (with possible collaboration with other task forces such as LODD and SWAN/SIOC) Identify neuroscience/life science databases (e.g., NIF databases, SWAN, Neurocommons, Bio2RDF, BioGateway, so on) Use of ontologies to help annotate data content Automatic extraction and conversion of local data into wiki page format with annotation Automatic import of annotated data/paper pages Interface with HCLS KB (e.g., DBPedia interfaces with Virtuoso – DBPedia supports both SPARQL Endpoint and Open linked data) Visualization and cross-language Community participation Neuroscience Semantic Web Semantic Wiki Text mining Linked Data Ontology Workflow

Acknowledgement Yale Ernest Lim Matt Holford Luis Marenco Pradeep Mutalik Tom Morse Perry Miller Gordon Shepherd UCSD Maryann Martone Stephen Larson

Thanks Questions?