BIRN Knowledge Engineering Working Group Chair: Gully APC Burns.

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Presentation transcript:

BIRN Knowledge Engineering Working Group Chair: Gully APC Burns

Core Capabilities Knowledge Representation and Reasoning Services within BIRN specifically geared towards applications Development of a knowledge engineering application development framework Support for ontology development within BIRN (but collaboration rather than competition with existing ontology tech. groups) Text mining tools and applications

Constituencies Users –Scientific Consortia + Communities (BIRN testbeds, NRPCs, CVRG, AlzForum, etc.) –Publishers (Elsevier, etc.) –Professional Societies (Society for Neuroscience, etc.) –Govt. Funding Agencies (NIH, NSF, etc.) –Disease Foundations (M. J. Fox Foundation, Kinetics Foundation, etc.) Partners –Ontology infrastructure developers (NIF, NCBO, GO, ScienceCommonns, OBI, SNOMED, IUPHAR, etc.) –Biocurators (Model Organism Databases, MGI, UniProt, etc.) –BioNLP specialists and developers (BioCREATIVE group, Andrey Rhzetsky, Larry Hunter, etc.) –Companies... (Chalklabs, etc)

We are closely aligned with the Data Integration Working Group

Required Knowledge Engineering Elements

Observations vs. Interpretations Observations –Based on experimental design (variables, constraints, measurements, protocol + statistics) –Not particularly contentious –Highly technical –Experimental methods conserved across domains, (i.e., histology in neuroscience is based on the same principles as histology in oncology) Interpretations –Based on ‘theories’ and schools of thought (massively variable between groups) –Highly contentious –Typically not well-defined (requiring very involved ontological engineering to represent) –Little conservation across domains (interpretive models in oncology are very different from those used in neuroscience).

Knowledge Engineering from Experimental Design (KE-f-ED)

“Novel neurotrophic factor CDNF protects midbrain dopamine neurons in vivo” Lindholm, P. et al. (2007), Nature, 448(7149): p * * *

Data and Relations underlying the statement: “CDNF protects nigral dopaminergic neurons in vivo” derived from Figure 3 of derived from Lindholm, P. et al. (2007), Nature, 448(7149): p labeling-density [CDNF (10ug)][4 weeks][cells] = 96 ± 3 % lesion vs. intact side labeling-density [CDNF (10ug)][4 weeks][fibers] = 74 ± 3 % lesion vs. intact side behavior-count [vehicle][4 weeks] > [CDNF (10ug)][4 weeks]

Topic Mapping CRISP data Ned Talley, Program Director for Channels, Synapses and Circuits at NINDS. Much interest across all institutes of NIH.

Team + Collaborators Existing BIRNCC Team –Jose Luis Ambite (ISI) –Naveen Ashish (UCI) –Gully Burns (ISI) –Hans Chalupsky (ISI) –Ed Hovy (UCI) –Tommy Ingulfsen (ISI) –Craig Knoblock (ISI) –Thomas Russ (ISI) –Jessica Turner (UCI) Invited to participate –Seth Ruffins (UCLA) –Alan Ruttenberg (ScienceCommons) Would like to invite... Lots of people!!! You???