Biomedical Annotation - Kevin Livingston

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  • Entity Centric
  • Document Centric
  • Rectangles are concepts we create, rounded rectangles are current ontological concepts. Orange objects are information content entities, blue objects are biomedical concepts.
  • Biomedical Annotation - Kevin Livingston

    1. 1. Biomedical AnnotationKevin Livingston, Ph.D.Postdoctoral FellowPharmacology Department, School of MedicineUniversity of Colorado Anschutz Medical Campus Kevin.Livingston@ucdenver.edu http://compbio.ucdenver.edu/Hunter_lab/Livingston
    2. 2. Biomedical researchers are interested inunderstanding their data in the context of all known background knowledge: curated databases & literature. 2
    3. 3. Pubmed Growth Rate 1100 25 1000 y = ~e0.0405x 900 R² = 0.99 20 800New Entries (thousands) Total Entries (millions) 700 15 600 500 y = ~e0.0402x R² = 0.94 10 400 300 200 5 100 2 journal 0 0 articles per 1987 1989 1991 1993 1995 1997 1999 2001 2003 2005 2007 2009 2011 973,499 PubMed entries in 2011 (>2,600 per day) minute! 3
    4. 4. Biomedical Data Sources Total Manual GO Annotations: 1,116,848 1,380 Total GO Database Annotations: s in 2012 132,425,702 PubMed Articles Referenced: 94,518 4
    5. 5. Annotation Consumers?• The linguistic community typically uses annotation as training data or for specific tasks – An abundance of tools that can produce annotations in the specific format of those resources – Tools for computational linguistics• Biomedical annotation typically used for curating, indexing, or enrichment analysis• But what about re-using annotations and tools in other contexts and for other purposes? 5
    6. 6. 6
    7. 7. Vision Intelligent DBs Application sOntologies Knowledge Base Text Mining Texts 7
    8. 8. Applications: Gene Centric 8
    9. 9. Applications: Document Centric 9
    10. 10. Annotation for Computation• Computer understandable• Composable• Provenance of compositions traceable 10
    11. 11. CRAFT: Colorado Richly Annotated Full Text corpushttp://bionlp-corpora.sourceforge.net/CRAFT/• 67 full text articles (+30 more reserved for future testing)• >560,000 Tokens• >21,000 Sentences• ~100,000 concept annotations to 7 different biomedical ontologies/terminologies• Penn Treebank markup for each sentence• Multiple output formats available 11
    12. 12. CRAFT Annotation hemopoiesis has agent results in regulation by transcription entity that has function corepressor activity biological binding regulation transcription results in protein coactivator results in regulation by activity interaction of regulates DNA protein transcriptionHematopoiesis is precisely orchestrated by lineage-specific DNA-binding proteins that regulate transcription in concert with coactivators and corepressors. GO GOCHEBI SO relation 12 BP MF
    13. 13. Applications: Annotating 13
    14. 14. Compositional Annotation & Knowledge vertebrate pigmentatio n occurs_in denotes subClassOf text annotation 3 TAXON:7742 GO:0043474 basedO basedO Vertebrata pigmentation n n hasBody hasBody CRAFTPMID:1473718 text annotation 1 text annotation 2 3 hasTarget hasTarget 14
    15. 15. Summary• Model that covers syntactic and semantic annotation – Linguistic annotation – Semantic annotation – Entity-based annotation• Capture complex content that is not necessarily best represented via a single URI – Created a GraphAnnotation that denotes a RDF named graph• Add kiao:basedOn to enable annotation compositions and provenance tracking – Annotation-level 15
    16. 16. AcknowledgementsUniversity of Colorado: • National ICT Australia• Hunter Lab – Karin Verspoor – Larry Hunter – Mike Bada • Funding: – Bill Baumgartner – NIH/NLM training grant – Chris Roeder – Andrew W. Mellon Foundation – Kevin Cohen – Carsten Goerg 16
    17. 17. Biomedical AnnotationKevin Livingston, Ph.D.Postdoctoral FellowPharmacology Department, School of MedicineUniversity of Colorado Anschutz Medical Campus Kevin.Livingston@ucdenver.edu http://compbio.ucdenver.edu/Hunter_lab/Livingston

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