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“Semantic Web” Applications in Bioinformatics

“Semantic Web” Applications in Bioinformatics. Amr AL-Hossary M.B.B.Ch. Agenda. Web & Semantic Web RDF & DRF Schema Elements Schema Name space Queries Pain, Design Patters, And limits, Applications of SW in Bioinformatics. Web Today. Documents for HUMANS Increasing dramatically

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“Semantic Web” Applications in Bioinformatics

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  1. “Semantic Web” Applications in Bioinformatics Amr AL-Hossary M.B.B.Ch

  2. Agenda • Web & Semantic Web • RDF & DRF Schema • Elements • Schema • Name space • Queries • Pain, Design Patters, And limits, • Applications of SW in Bioinformatics

  3. Web Today • Documents for HUMANS • Increasing dramatically • Hard to process on semantic level • e.g. searching for “give her a ring” doesn’t return “engage her”. • Solution (semantic web) • annotating definitions • abstract representation of classes & relations

  4. What is the Semantic Web?

  5. Myths about Semantic Web… • is Top-Down • needs ontologies at the beginning • requires all information to be converted to RDF • must be centralized • handles only binary relations • requires the entire graph to exist on one memory store

  6. Truths • A means of describing (a Web of) Data • A system defining and incorporating semantics • A mechanism for making statements on things • A format for associating metadata • A strategy for federating data systems (with or without triplestore)

  7. Needs • shareddefinitions of knowledge domains, i.e. ontologies, • association of concepts to existing data, • metadatainformation describing information sources and contents, • search tools able to make the best use of this additional information.

  8. RDF • (Directed) graph data model • Set of Binary relations (triples) • Subject Predicate Object • NOT like DBMS: Absence of a relation does NOT mean it is not present. • XML and RDF/OWL are inherently different • XML = thesaurus document structure • RDF = thesaurus document content

  9. Recombinant Data Space • RDF is about Graphs rather than statements • Separate Graphs can be merged easily into one aggregate graph • Graphs can be filtered and pivoted, without losing meaning

  10. Recombinant Data Space Sun of Studied Medicine Zaynab Ali Works in Amr Amr Amr N U Works in N U Abolhouda

  11. Recombinant Data Space Medicine Zaynab Ali Amr N U Abolhouda

  12. Recombinant Data Space Medicine Amr N U Abolhouda

  13. RDF Elements • Resources R • Properties P • Literal Values L • Assertions "R P L" or "R P R" • Namespaces

  14. RDF Schema • RDF Schema (RDFS) is a vocabulary to create vocabularies... • Comparable to XML Schema or XML DTD • Used to standardize which “tags” the creator of a graph is allowed to use for annotating resources • Introduces notions such as "Class" and "Subclass„ • Helps define which relations a resource of a certain type may have

  15. RDFS Namespace Elements • X rdf:type rdfs:class • denotes that resource X is a class • R rdf:type rdf:Property • denotes that resource R is a property • R rdfs:domain X • denotes that the subject of R must be an X • R rdfs:range Y • denotes that the object of R must be a Y

  16. Cited from http://www.nettab.org/2007/slides/Tutorial_Stoermer.pdf

  17. Query Languages • RDQL • SERQL • SPARQL (upcoming W3C Standard)

  18. SPARQL Example PREFIX nettab <http://www.nettab.org/tutorial-ns#> SELECT ?x ?y ?z WHERE { ?x nettab:givesTalk ?z } Matching triple: Subject: http://www.nettab.org/tutorial-ns#hst Predicate: http://www.nettab.org/tutorial-ns#givesTalk Object: http://www.know-who.net/talks/nettab.ppt Cited from http://www.nettab.org/2007/slides/Tutorial_Stoermer.pdf

  19. RDF Limitation (& Design Patterns) • N-ary Relations • It understands only Binary ralations • Amr Leads Pulse in 2009 • Exceptions • Human RBCs are Unnucleated

  20. Example Applications of Semantic Web in Bioinformatics

  21. Vocabularies (Thesauri) • Example Thesauri in Medicine • UMLS • SNOMED • MESH • Galen

  22. OKKAM (for ENS)

  23. Addison’s disease in medical vocabularies • Synonyms • Addisonian syndrome • Bronzed disease • Addison melanoderma • Asthenia pigmentosa • Primary adrenal deficiency • Primary adrenal insufficiency • Primary adrenocortical insufficiency • Chronic adrenocortical insufficiency Eponym Symptoms Clinical Varieties

  24. Disease/Diagnosis SNOMED International Disease of Endocrine System Disease of the Adrenal Gland Addison’s Disease

  25. Disease MeSH Endocrine Disease Adrenal Gland Disease Adrenal Gland Hypofunction Addison’s Disease

  26. AOD Endocrine Disorder Adrenal Disorder Adrenal Cortical Disorder Corticoadrenal insufficiency Addison’s Disease

  27. Read Codes Endocrine Diseases Disorder of Adrenal Gland Hypoadrenalism Adrenal Hypofunction Corticoadrenal insufficiency Addison’s Disease

  28. Organizing concept SNOMED MeSH ADO Read Codes UMLS Endocrine Diseases Adrenal Gland Diseases Adrenal Cortex Diseases Hypoadrenalism Adrenal Gland Hypofunction Adrenal cortical hypofunction Addison’s Disease

  29. UMLS vocabularies available in RDF/OWL • NCI Thesaurus (OWL) • http://ncicb.nci.nih.gov/core/EVS • Gene Ontology • http://www.geneontology.org • Repository of biomedical ontologies (OBO, OWL) • http://www.bioontology.org/ncbo/faces/index.xhtml

  30. User-defined Datatypes • Based on syntax used in Protégé • Semantics derived from XML Schema datatypes • For numbers: min, max, digits, fraction digits • For strings: length (min, max, equal), regular • expression patterns • Class (Teenager complete restriction (age someValuesFrom (datatype(xsd:int minInclusive(“13”^^xsd:int) maxInclusive(“19”^^xsd:int)))))

  31. Biological Pathway eXchange (BioPAX) • Represent: • Metabolic pathways • Signaling pathways • Protein-protein, molecular interactions • Gene regulatory pathways • Genetic interactions • Community effort: pathway databases distribute pathway information in standard format

  32. cPath • cPath is a database and software suite for storing, visualizing, and analyzing biological pathways

  33. cPath Key Features • Identifier mapping system e.g. proteins • Scalable pathway data aggregation • Simple web interface for browse and query • Standard web service API for application communication • 100% open source • Java, Tomcat, MySQL, Lucene, Struts, YUI • Local installation and customization

  34. iHOP (information Hyperlink Over Protein)Adding value via text mining

  35. Pathway Commons

  36. A Genome – PhenomeIntegrated Approach forMining Disease-Causal Genesusing Semantic Web Gudivada Ranga Chandra Email : gudx6u@cchmc.org Department of Biomedical Engineering/University of Cincinnati Division of Biomedical Informatics/ Cincinnati Children’s Hospital Medical Center

  37. Questions?

  38. References • RDF standard and technologies (presentation)Heiko Stoermer, University of Trento, Italy • http://www.nettab.org/2007/slides/Tutorial_Stoermer.pdf • The Unified Medical Language System (UMLS) and the Semantic Web (presentation)Olivier Bodenreider, National Library of Medicine, USA • http://www.nettab.org/2007/slides/Tutorial_Bodenreider.pdf • Semantic Web for Health Care and Life Science Interest Group: A Vision for Advancing Research Communities (presentation)Eric Neumann, Teranode Co., USA. • http://www.nettab.org/2007/slides/SemanticWeb_Neumann.pdf • OKKAM web site • http://www.okkam.org/ • Unified Medical Language System (UMLS) • http://www.nlm.nih.gov/research/umls/ • Biological Pathway eXchange (BioPAX) • http://www.biopax.org/ • cPath: Demo Site • http://cbio.mskcc.org/cpath/ • iHOP (information Hyperlink Over Protein) • http://www.ihop-net.org/UniPub/iHOP/ • Pathway Commons • http://www.pathwaycommons.org/pc/

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