Seed-based Generation of Personalized Bio-Ontologies for Information Extraction Cui Tao & David W. Embley Data Extraction Research Group Department of.

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Presentation transcript:

Seed-based Generation of Personalized Bio-Ontologies for Information Extraction Cui Tao & David W. Embley Data Extraction Research Group Department of Computer Science Brigham Young University Supported by NSF

Personalized Information Harvesting Biology domain  huge (other domains too) Data collection – Many (web) sources – Only a tiny subpart wanted – Personalized view Personalized extraction ontology – Creation: Form specification – Application: Seed-based harvesting

Example Harvest information about large proteins in humans and the functions of these proteins – Find proteins in humans that are >20 kDa – Find all the proteins in humans that serve as receptors –... Information sources  various online repositories – NCBI – Gene Cards – The Gene Ontology – GPM Proteomics Database – …

Extraction Ontology Instance: ^\d{1,5}(\.\d{1,2})? Context: weight|wght|wt\. Unit: kilodaltons?|kdas?|kds?|das?|daltons? … T-complex protein 1 subunit theta TCP-1-theta CCT-theta Renal carcinoma antigen NY-REN-15 …

Extraction Ontology Instance: ^\d{1,5}(\.\d{1,2})? Context: weight|wght|wt\. Unit: kilodaltons?|kdas?|kds?|das?|daltons? … T-complex protein 1 subunit theta TCP-1-theta CCT-theta Renal carcinoma antigen NY-REN-15 …

Can We Make Construction Easier? Forms – General familiarity – Reasonable conceptual framework – Appropriate correspondence Transformable to ontological descriptions Capable of accepting source data Instance recognizers – Some pre-existing instance recognizers – Lexicons Need for a full extraction ontology?

Form Creation User Interface Basic form-construction facilities: single-entry field multiple-entry field nested form …

Created Sample Form

Generated Ontology View

Source-to-Form Mapping Establishing a Seed

Source-to-Form Mapping Establishing a Seed

Source-to-Form Mapping Establishing a Seed

Source-to-Form Mapping Establishing a Seed

Almost Ready to Harvest … Need reading path: DOM-tree structure Need to resolve mapping problems – Split/Merge – Union/Selection

Almost Ready to Harvest … Need reading path: DOM-tree structure Need to resolve mapping problems – Split/Merge – Union/Selection Voltage-dependent anion-selective channel protein 3 VDAC-3 hVDAC3 Outer mitochondrial membrane Protein porin 3 Name

Almost Ready to Harvest … Need reading path: DOM-tree structure Need to resolve mapping problems – Split/Merge – Union/Selection Voltage-dependent anion-selective channel protein 3 VDAC-3 hVDAC3 Outer mitochondrial membrane Protein porin 3 Name

Almost Ready to Harvest … Need reading path: DOM-tree structure Need to resolve mapping problems – Split/Merge – Union/Selection Name T-complex protein 1 subunit theta TCP-1-theta CCT-theta Renal carcinoma antigen NY-REN-15

Almost Ready to Harvest … Need reading path: DOM-tree structure Need to resolve mapping problems – Split/Merge – Union/Selection Name T-complex protein 1 subunit theta TCP-1-theta CCT-theta Renal carcinoma antigen NY-REN-15

Can Now Harvest Name

Can Now Harvest Name protein epsilon Mitochondrial import stimulation factor Lsubunit Protein kinase C inhibitor protein-1 KCIP E

Can Now Harvest Name Voltage-dependent anion-selective channel protein 3 VDAC-3 hVDAC3 Outer mitochondrial membrane Protein porin 3

Can Now Harvest Name Tryptophanyl-tRNA synthetase, mitochondrial precursor EC Tryptophan—tRNA ligase TrpRS (Mt)TrpRS

Harvesting Populates Ontology

Also helps adjust ontology constraints

Can Harvest from Additional Sites Name T-complex protein 1 subunit theta TCP-1-theta CCT-theta Renal carcinoma antigen NY-REN-15

Larger Picture Information Harvesting – Not only for biology, but for any application – Not only from one site, but from many sites Opportunities – Extraction ontology creation – Automating site-to-site information harvesting – Automatic semantic annotation – Data/Ontology transformations

Extraction Ontology Creation Lexicons Name protein epsilon Mitochondrial import stimulation factor Lsubunit Protein kinase C inhibitor protein-1 KCIP E Name T-complex protein 1 subunit theta TCP-1-theta CCT-theta Renal carcinoma antigen NY-REN-15 Name Tryptophanyl-tRNA synthetase, mitochondrial precursor EC Tryptophan—tRNA ligase TrpRS (Mt)TrpRS … protein epsilon Mitochondrial import stimulation factor Lsubunit Protein kinase C inhibitor protein-1 KCIP E … T-complex protein 1 subunit theta TCP-1-theta CCT-theta Renal carcinoma antigen NY-REN-15 … Tryptophanyl-tRNA synthetase, mitochondrial precursor EC Tryptophan—tRNA ligase TrpRS (Mt)TrpRS …

Automatic Source-to-Form Mapping

Automatic Semantic Annotation

Extraction Ontology Creation Instance Recognizers Number Patterns Context Keywords and Phrases

Automatic Source-to-Form Mapping

Automatic Semantic Annotation Recognize and annotate with respect to an ontology

Ontology Transformation OWL & RDF: standard ontology languages XML & XMLS: data exchange Forms: form filling to populate an ontology

Ontology Transformation Transformations to and from all

Contributions Personalized ontology creation Mapping from sources Information harvesting Opportunities for further work – Extraction ontology creation – Semantic Annotation – Data/Ontology transformations