Tutorial what is_an_ontology_ncbo_march_2012

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Tutorial what is_an_ontology_ncbo_march_2012

  1. 1. What is an Ontology and What is it Useful For? Barry Smith http://ontology.buffalo.edu/smith 1
  2. 2. A brief history of the Semantic Web• html demonstrated the power of the Web to allow sharing of information• can we use semantic technology to create a Web 2.0 which would allow algorithmic reasoning with online information based on XLM, RDF and above all OWL (Web Ontology Language)?• can we use RDF and OWL to break down silos, and create useful integration of on-line data and information 2
  3. 3. people tried, but the more they were successful, they more they failedOWL breaks down data silos via controlled vocabularies for the description of data dictionariesUnfortunately the very success of this approach led to the creation of multiple, new, semantic silos – because multiple ontologies are being created in ad hoc ways 3
  4. 4. reasons for this effect• Tim Berners Lee mentality – let a million ‘lite ontologies bloom’, and somehow intelligence will be created – ‘links’ can mean anything (à la html)• shrink-wrapped software mentality – you will not get paid for reusing old and good ontologies• requirements-driven software development• reducing potential secondary uses 4/24
  5. 5. Ontology success stories, and some reasons for failure •A fragment of the “Linked OpenData” in the biomedical domain 5
  6. 6. What you get with ‘mappings’ HPO: all phenotypes (excess hair loss, duck feet) 6
  7. 7. What you get with ‘mappings’ HPO: all phenotypes (excess hair loss, duck feet ...)NCIT: all organisms 7
  8. 8. What you get with ‘mappings’ all phenotypes (excess hair loss, duck feet)all organisms allose (a form of sugar) 8
  9. 9. What you get with ‘mappings’ all phenotypes (excess hair loss, duck feet)all organisms allose (a form of sugar)Acute Lymphoblastic Leukemia (A.L.L.) 9
  10. 10. 10
  11. 11. Mappings are hardThey are fragile, and expensive to maintainNeed a new authority to maintain, yielding new risk of forkingThe goal should be to minimize the need for mappingsInvest resources in disjoint ontology modules which work well together – reduce need for mappings to minimum possible 11
  12. 12. Why should you care?• you need to create systems for data mining and text processing which will yield useful digitally coded output• if the codes you use are constantly in need of ad hoc repair huge resources will be wasted• relevant data will not be found• serious reasoning will be defeated from the start 12/24
  13. 13. 13
  14. 14. 14
  15. 15. … 15
  16. 16. How to do it right?• how create an incremental, evolutionary process, where what is good survives, and what is bad fails• where the number of ontologies needing to be linked is small• where links are stable• create a scenario in which people will find it profitable to reuse ontologies, terminologies and coding systems which have been tried and tested 16/24
  17. 17. Uses of ‘ontology’ in PubMed abstracts 17
  18. 18. By far the most successful: GO (Gene Ontology) 18
  19. 19. GO provides a controlled system of termsfor use in annotating (describing, tagging) data• multi-species, multi-disciplinary, open source• contributing to the cumulativity of scientific results obtained by distinct research communities• compare use of kilograms, meters, seconds in formulating experimental results 19
  20. 20. Hierarchical view representingrelations between represented 20types
  21. 21. Anatomical Anatomical Space StructureOrgan Cavity Organ Organ Organ Part Subdivision Cavity Serous Sac Serous Sac Organ Organ Cavity Cavity Serous Sac Component Subdivision Tissue Subdivisionis_a Pleural Sac Pleural Sac Pleura(Wall Pleural Pleura(Wall Pleural of Sac) of Sac) Cavity of Cavity Parietal Parietal Pleura t_ Pleura Visceral Visceral Interlobar Pleura Pleura Interlobar r recess recess Mediastinal pa Mediastinal Pleura Pleura Mesothelium Mesothelium of Pleura of Pleura 21 Foundational Model of Anatomy (FMA)
  22. 22. US $100 mill. invested in literature and data curation using GO over 11 million annotations relating gene products described in the UniProt, Ensembl and other databases to terms in the GO experimental results reported in 52,000 scientific journal articles manually annoted by expert biologists using GO 22
  23. 23. Reasons why GO has been successfulIt is a system for prospective standardization built with coherent top level but with content contributed and monitored by domain specialistsBased on community consensusUpdated every nightClear versioning principles ensure backwards compatibility; prior annotations do not lose their valueInitially low-tech to encourage users, with movement to more powerful formal approaches (including OWL-DL – though GO community still recommending caution) 23
  24. 24. GO has learned the lessons of successful cooperation• Clear documentation• The terms chosen are already familiar• Fully open source (allows thorough testing in manifold combinations with other ontologies)• Subjected to considerable third-party critique• Rapid turnaround tracker and help desk• Usable also for education• Focus on reality 24
  25. 25. Why is the focus on reality importantEach community, each local data structure, has its own conceptualizationWhat shall serve as benchmark for the integration of the data generated by data communities?Answer: Reality, as understood by bench scientistsConclusion: Bench scientists have to be involved in the construction and coordination of ontologies 25
  26. 26. Data structures and ontologies have different purposes Information models and ontologies are at different levels • The purpose of an information model is:to specify valid data structures to carry information • To constrain the data structures to just those which a given software system can process The purpose of an ontology is to represent the world 26
  27. 27. Data structures and ontologies have different characteristics All persons have a sex However not all data structures about people have a field for sexInformation structures are intrinsicallyclosedWe can describe them completelyOntologies are intrinsically open We can never describe the real world completely 27
  28. 28. Benefits of GOEstablishing a bridge between the molecular/gene level and higher order biology – you get nothing by just looking at genes.Building up a larger picture of biological systems as a mosaic of areas studied in depth by one or other of the model organism databases (but never all, and not all in any one)Creating a view to link studies on different organisms. 28
  29. 29. Sample Gene Array Data 29
  30. 30. where in the body ? what kind of disease process ? need for semantic annotation of data 30
  31. 31. natural language labels to make the data cognitively accessible to human beings 31
  32. 32. compare: legends for maps 32
  33. 33. ontologies are legends for data 33
  34. 34. annotation with Gene Ontology supports reusability of data supports search of data by humanssupports reasoning with data by humans and machines 34
  35. 35. GO has been amazingly successful in overcoming the data balkanization problembut it covers only generic biological entities ofthree sorts: – cellular components – molecular functions – biological processes and it does not provide representations of diseases, symptoms, … 35
  36. 36. CONTINUANT OCCURRENT RELATION TO TIME INDEPENDENT DEPENDENTGRANULARITY Anatomical Organism Organ ORGAN AND Entity (NCBI Function ORGANISM (FMA, Taxonomy) (FMP, CPRO) Phenotypic Biological CARO) Quality Process (PaTO) (GO) CELL AND Cellular Cellular Cell CELLULAR Component Function (CL) COMPONENT (FMA, GO) (GO) Molecule Molecular Function Molecular Process MOLECULE (ChEBI, SO, (GO) (GO) RnaO, PrO) Original OBO Foundry ontologies (Gene Ontology in yellow) 36
  37. 37. CONTINUANT OCCURRENT RELATION TO TIME INDEPENDENT DEPENDENTGRANULARITY Anatomical Organism Organ ORGAN AND Entity (NCBI Function ORGANISM (FMA, Taxonomy) (FMP, CPRO) Phenotypic environments CARO) Biological Quality Process (PaTO) (GO) are here CELL AND Cellular Cellular Cell CELLULAR Component Function (CL) COMPONENT (FMA, GO) (GO) Molecule Molecular Function Molecular Process MOLECULE (ChEBI, SO, (GO) (GO) RnaO, PrO) Environment Ontology 37
  38. 38. CONTINUANT OCCURRENT RELATION TO TIME INDEPENDENT DEPENDENTGRANULARITY COMPLEX OF Family, Community, Population Population ORGANISMS Deme, Population Phenotype Process Anatomical Organ ORGAN AND Organism Entity Function ORGANISM (NCBI (FMA, (FMP, CPRO) Phenotypic Taxonomy) Biological CARO) Quality Process (PaTO) (GO) CELL AND Cellular Cellular Cell CELLULAR Component Function (CL) COMPONENT (FMA, GO) (GO) Molecule Molecular Function Molecular Process MOLECULE (ChEBI, SO, (GO) (GO) RnaO, PrO) http://obofoundry.org 38
  39. 39. Ontology success stories, and some reasons for failure• 39
  40. 40. CONTINUANT OCCURRENT RELATION TO TIME INDEPENDENT DEPENDENTGRANULARITY COMPLEX OF Family, Community, Population Population ORGANISMS Deme, Population Phenotype Process Anatomical Organ ORGAN AND Organism Entity Function ORGANISM (NCBI (FMA, (FMP, CPRO) Phenotypic Taxonomy) Biological CARO) Quality Process (PaTO) (GO) CELL AND Cellular Cellular Cell CELLULAR Component Function (CL) COMPONENT (FMA, GO) (GO) Molecule Molecular Function Molecular Process MOLECULE (ChEBI, SO, (GO) (GO) RnaO, PrO) http://obofoundry.org 40
  41. 41. The OBO Foundry: a step-by-step,evidence-based approach to expand the GO  Developers commit to working to ensure that, for each domain, there is community convergence on a single ontology  and agree in advance to collaborate with developers of ontologies in adjacent domains. http://obofoundry.org 41
  42. 42. OBO Foundry Principles Common governance (coordinating editors) Common training Common architecture to overcome Tim Berners Lee-ism: • simple shared top level ontology • shared Relation Ontology: www.obofoundry.org/ro 42
  43. 43. Open Biomedical Ontologies Foundry Seeks to create high quality, validated terminology modules across all of the life sciences which will be• one ontology for each domain, so no need for mappings• close to language use of experts• evidence-based• incorporate a strategy for motivating potential developers and users• revisable as science advances 43
  44. 44. A prospective standarddesigned to guarantee interoperability of ontologiesfrom the very start (and to keep out weeds)initial set of 10 criteria tested in the annotation of scientific literature model organism databases life science experimental results 44
  45. 45. ORTHOGONALITYmodularity ensures • annotations can be additive • division of labor amongst domain experts • high value of training in any given module • lessons learned in one module can benefit work on other modules • incentivization of those responsible for individual modules 45
  46. 46. Benefits of coordinationCan profit from lessons learned through mistakesmade by othersCan more easily reuse what is made by othersCan more easily inspect and criticize results ofothers’ workLeads to innovations (e.g. Mireot in strategies forcombining ontologies and for importing terms fromother ontologies) 46
  47. 47. Problems with the OBO Foundry1. the results are over-complex for almost all users 2. high quality ontology development is slow, slow, slowFor 1., views (Brinkley, Uvic, ontodog, …) For 2., the hub and spokes model 47
  48. 48. The Hub and Spokes Model“Constructing a lattice of Infectious Disease Ontologies from a Staphylococcus aureus Isolate Repository”Albert Goldfain, Lindsay Cowell and Barry Smith, Proceeedings of the Third International Conference on Biomedical Ontology, Graz, July 22-25, 2012, forthcoming. 48
  49. 49. Infectious Disease Ontology (IDO) – IDO Core: • General terms in the ID domain. • A hub for all IDO extensions. – IDO Extensions: • Disease specific. • Developed by subject matter experts.• Provides: – Clear, precise, and consistent natural language definitions – Computable logical representations (OWL, OBO)
  50. 50. How IDO evolvesIDOMAL IDOCore IDOHIV CORE and SPOKES:IDOFLU Domain IDORatSa IDORatStrep ontologies IDOSa IDOStrep IDOMRSa IDOAntibioticResistant SEMI-LATTICE: By subject matter experts in different IDOHumanSa IDOHumanStrep communities of interest. IDOHumanBacterial
  51. 51. IDO Core• Contains general terms in the ID domain: – E.g., ‘colonization’, ‘pathogen’, ‘infection’• A contract between IDO extension ontologies and the datasets that use them.• Intended to represent information along several dimensions: – biological scale (gene, cell, organ, organism, population) – discipline (clinical, immunological, microbiological) – organisms involved (host, pathogen, and vector types)
  52. 52. Sample IDO Definitions• Host of Infectious Agent (BFO Role): A role borne by an organism in virtue of the fact that its extended organism contains an infectious agent.• Extended Organism (OGMS): An object aggregate consisting of an organism and all material entities located within the organism, overlapping the organism, or occupying sites formed in part by the organism.• Infectious Agent: A pathogen whose pathogenic disposition is an infectious disposition.
  53. 53. IDO and IDOSa• Scale of the infection (disorder)12/10/2010 53 from Shetty, Tang, and Andrews, 2009
  54. 54. Differentiated Staphylococcus aureus (Sa)by:AntibioticResistance { MSSa MRSaPathogenesisLocationType { HA-MRSa CA-MRSaGeographicRegion { UK CA-MRSa Australian CA-MRSa Various Differentia { Specific Strains
  55. 55. Sample Application: A lattice of infectious disease application ontologies from NARSA isolate dataNetwork on Antimicrobial Resistancein Staphylococcus aureus–http://www.narsa.net/content/staphLinks.jspTrue personalized medicine – YourDiseaseOntology
  56. 56. Ways of differentiating Staphylococcus aureus infectious diseases• Infectious Disease – By host type – By (sub-)species of pathogen – By antibiotic resistance – By anatomical site of infection• Bacterial Infectious Disease – By PFGE (Strain) – By MLST (Sequence Type) – By BURST (Clonal Complex)• Sa Infectious Disease – By SCCmec type • By ccr type • By mec class – spa type http://www.sccmec.org/Pages/SCC_ClassificationEN.html
  57. 57. NRS701’s resistance to clindamycinido.owlnarsa.owl ndf-rtnarsa-isolates.owl
  58. 58. R T U New York State Center of Excellence in Bioinformatics & Life Sciences Ontologies make data collections comparable Characteristics Cases ch1 ch2 ch3 ch4 ch5 ch6 ... case1 case2 case3 case4 case5 case6 ... Characteristics Cases ch1 ch2 ch3 ch4 ch5 ch6 ... Characteristics case1Cases ch1 ch2 ch3 ch4 ch5 ch6 ... case2 case3case1 case4case2 case5case3 case6case4 ...case5case6 Linking the variables of distinct data collections ... to a realism-based ontology.
  59. 59. R T U New York State Center of Excellence in Bioinformatics & Life Sciences OPMQoL: an Ontology for pain- related disablement, mental health and quality of life Werner Ceusters 1R01DE021917-01A1 National Institute of Dental and Craniofacial Research (NIDCR).
  60. 60. IASP definition for ‘pain’: – ‘an unpleasant sensory and emotional experience associated with actual or potential tissue damage, or described in terms of such damage’;which asserts: – a common phenomenology (‘unpleasant sensory and emotional experience’) to all instances of pain, – the recognition of three distinct subtypes of pain involving, respectively: 1. actual tissue damage, 2. what is called ‘potential tissue damage’, and 3. a description involving reference to tissue damage whether or not there is such damage.
  61. 61. A data collection consists of at least 1 data item,each data item belonging to exactly 1 collection 1 data collection 1..* data item
  62. 62. Data dictionaries provide information about data items and data collections 1 explained-in data dictionary uses 1 used-for 1..* 1 data collection explains 1..* 1..* data item
  63. 63. Data dictionaries provide also information aboutterminologies and assessment instruments used for data generation, in addition to information about the collection’s structure uses 1..* used uses for 0..* terminology 1..* uses assessment used for 0..* 1..* instrument 1 used-in explained-in data dictionary 0..* uses 1 used-for 1..* 1 data collection explains 1..* 1..* data item
  64. 64. Relation of Terminology component to Data componentTerminology component uses 1..* used uses for 0..* terminology 1..* uses assessment used for 0..* 1..* instrument 1 used-in explained-in data dictionary 0..* uses 1 Data component used-for 1..* 1 data collection explains 1..* 1..* data item
  65. 65. Terminology links terms to ‘concepts’Terminology component uses 1..* used 1 uses for 0..* terminology 1..* uses assessment 1..* used used in for 0..* 1..* instrument 0..* term 1 used-in uses 0..* expressed- explained-in data dictionary 0..* by uses 1 Data component 1..* used-for 1..* 1 means 1 data collection explains broader concept 1..* 1..* narrower 1..* data item 1..*
  66. 66. Not ‘concepts’ are of interest, but entities in realityTerminology component uses 1..* used 1 uses for 0..* terminology 1..* uses assessment 1..* used used in for 0..* 1..* instrument 0..* term 1 used-in uses 0..* expressed- explained-in data dictionary 0..* by uses 1 Data component 1..* used-for 1..* 1 means 1 data collection explains broader concept 1..* 1..* narrower 1..* data item 1..*Ontology entitycomponent
  67. 67. It is real entities that should be denoted in ontologiesTerminology component uses 1..* used 1 uses for 0..* terminology 1..* uses assessment 1..* used used in for 0..* 1..* instrument 0..* term 1 used-in uses 0..* expressed- explained-in data dictionary 0..* by uses 1 Data component 1..* used-for 1..* 1 means 1 data collection explains broader concept 1..* 1..* narrower 1..* data item 1..* ontology 1 denotes denoted 1..*Ontology entity 1 by 0..* denotatorcomponent reference ontology
  68. 68. Application ontologies cover the domains of the sourcesTerminology component uses 1..* used 1 uses for 0..* terminology 1..* uses assessment 1..* used used in for 0..* 1..* instrument 0..* term 1 used-in used 1 uses 0..* expressed- explained-in data dictionary 0..* for by uses 1 Data component 1..* used-for 1..* uses 1 1 used-for means 1 data collection assessment explains 1..* broader instrument concept 1..* 1..* uses 1 ontology narrower 1..* data item data collection 1..* ontology application ontology ontology 1 denotes denoted 1..*Ontology entity 1 by 0..* denotatorcomponent reference ontology
  69. 69. Bridging axioms link data to ontologies and terminologiesTerminology component uses 1..* used 1 uses for 0..* terminology 1..* uses assessment 1..* used used in for 0..* 1..* instrument 0..* term 1 used-in used 1 uses 0..* expressed- explained-in data dictionary 0..* for by uses 1 Data component 1..* used-for 1..* uses 1 1 used-for means 1 data collection assessment explains 1..* broader instrument concept 1..* 1..* uses 1 ontology expresses 0..1 narrower 1..* data item data collection 1..* ontology used application uses for uses corresponds-to representational bridging axiom used-for ontology 1..* 0..* 1..* 1 0..* artifact ontology 1 denotes denoted 1..*Ontology entity 1 by 0..* denotatorcomponent reference ontology
  70. 70. top level Basic Formal Ontology (BFO) Ontology for Information Artifact Biomedical Spatial Ontology mid-level Ontology Investigations (BSPO) (IAO) (OBI) Anatomy Ontology (FMA*, CARO) Infectious Disease Environment Ontology Cellular Cell Ontology (IDO*) Component Ontology (EnvO) Ontologydomain level (CL) (FMA*, GO*) Phenotypic Biological Quality Process Ontology Ontology (GO*) Subcellular Anatomy Ontology (SAO) (PaTO) Sequence Ontology (SO*) Molecular Function Protein Ontology (GO*) (PRO*) OBO Foundry Modular Organization 71
  71. 71. BFO: the very top Continuant Occurrent (Process, Event)Independent Dependent Continuant Continuant
  72. 72. CONTINUANT OCCURRENT RELATION TO TIME INDEPENDENT DEPENDENTGRANULARITY Anatomical Organism Organ ORGAN AND Entity (NCBI Function ORGANISM (FMA, Taxonomy) (FMP, CPRO) Phenotypic Biological CARO) Quality Process (PaTO) (GO) CELL AND Cellular Cellular Cell CELLULAR Component Function (CL) COMPONENT (FMA, GO) (GO) Molecule Molecular Function Molecular Process MOLECULE (ChEBI, SO, (GO) (GO) RnaO, PrO) 73
  73. 73. RELATION CONTINUANT OCCURRENT TO TIMEGRANULARITY INDEPENDENT DEPENDENT Anatomical Organism Organ Organism-Level ORGAN AND Entity (NCBI Function Process ORGANISM (FMA, Taxonomy) (FMP, CPRO) Phenotypic (GO) CARO) Quality (PaTO) CELL AND Cellular Cellular Cell Cellular Process CELLULAR Component Function (CL) (GO) COMPONENT (FMA, GO) (GO) Molecule Molecular Molecular Function MOLECULE (ChEBI, SO, Process (GO) RnaO, PrO) (GO) obofoundry.org
  74. 74. Basic Formal Ontology continuant occurrentindependent dependent continuant continuant cellular molecular biologicalcomponent function processes
  75. 75. BFO: The Very Top continuant occurrentindependent dependent continuant continuant quality function role disposition
  76. 76. Basic Formal Ontologytypes Continuant Occurrent process, event Independent Dependent Continuant Continuant thing quality .... ..... .......instances
  77. 77. Basic of BFO in GO Continuant Occurrent biologicalIndependent Dependent process Continuant Continuant cellular molecular..... ..... ........component function
  78. 78. Experience with BFO in building ontologies provides• a community of skilled ontology developers and users (google user group has 118 members)• associated logical tools• documentation for different types of users• a methodology for building conformant ontologies by starting with BFO and populating downwards
  79. 79. Example: The Cell Ontology
  80. 80. Users of BFOPharmaOntology (W3C HCLS SIG)MediCognos / Microsoft HealthvaultCleveland Clinic Semantic Database in Cardiothoracic SurgeryMajor Histocompatibility Complex (MHC) Ontology (NIAID)Neuroscience Information Framework Standard (NIFSTD) and Constituent OntologiesInterdisciplinary Prostate Ontology (IPO)Nanoparticle Ontology (NPO): Ontology for Cancer Nanotechnology ResearchNeural Electromagnetic Ontologies (NEMO)ChemAxiom – Ontology for Chemistry 81 :.
  81. 81. Users of BFOGO Gene OntologyCL Cell OntologySO Sequence OntologyChEBI Chemical OntologyPATO Phenotype (Quality) OntologyFMA Foundational Model of Anatomy OntologyChEBI Chemical Entities of Biological InterestPRO Protein OntologyPlant OntologyEnvironment OntologyOntology for Biomedical InvestigationsRNA Ontology 82 :.
  82. 82. Users of BFOOntology for Risks Against Patient Safety (RAPS/REMINE)eagle-i an VIVO (NCRR)IDO Infectious Disease Ontology (NIAID)National Cancer Institute Biomedical Grid Terminology (BiomedGT)US Army Biometrics OntologyUS Army Command and Control OntologySleep Domain OntologySubcellular Anatomy Ontology (SAO)Translaftional Medicine On (VO)Yeast Ontology (yOWL)Zebrafish Anatomical Ontology (ZAO) 83 :.
  83. 83. Basic Formal Ontology continuant occurrentindependent dependent continuant continuant organism 84
  84. 84. Continuants• continue to exist through time, preserving their identity while undergoing different sorts of changes• independent continuants – objects, things, ...• dependent continuants – qualities, attributes, shapes, potentialities ... 85
  85. 85. Occurrents• processes, events, happenings – your life – this process of accelerated cell division 86
  86. 86. Qualitiestemperatureblood pressuremass... are continuants they exist through time while undergoing changes 87
  87. 87. Qualitiestemperature / blood pressure / mass ... are dimensions of variation within the structure of the entity a quality is something which can change while its bearer remains one and the same 88
  88. 88. A Chart representing howJohn’s temperature changes 89
  89. 89. A Chart representing howJohn’s temperature changes 90
  90. 90. John’s temperature,the temperature he has throughout hisentire life, cycles through differentdeterminate temperatures from onetime to the nextJohn’s temperature is a physiologyvariable which, in thus changing,exerts an influence on other physiologyvariables through time 91
  91. 91. BFO: The Very Top continuant occurrentindependent dependent continuant continuant quality temperature 92
  92. 92. Blinding Flash of the Obviousindependent dependent continuant continuant qualityorganism temperature types John’s John temperature instances 93
  93. 93. Blinding Flash of the Obviousindependent dependent continuant continuant qualityorganism temperature types John’s John temperature instances 94
  94. 94. Blinding Flash of the Obvious inheres_in .organism temperature types John’s John temperature instances 95
  95. 95. temperature types37ºC 37.1ºC 37.2ºC 37.3ºC 37.4ºC 37.5ºCinstantiates instantiates instantiates instantiates instantiates instantiates at t1 at t2 at t3 at t4 at t5 at t6 John’s temperature instances 96
  96. 96. human typesembryo fetus neonate infant child adult instantiates instantiates instantiates instantiates instantiates instantiates at t1 at t2 at t3 at t4 at t5 at t6 John instances 97
  97. 97. Temperature subtypesDevelopment-stage subtypesare threshold divisions (hence we donot have sharp boundaries, and wehave a certain degree of choice, e.g. inhow many subtypes to distinguish,though not in their ordering) 98
  98. 98. independent dependent continuant continuant qualityorganism temperature types John’s John temperature instances 99
  99. 99. independent dependent occurrent continuant continuant quality processorganism course of temperature temperature changes John’s John’s John temperature temperature history 100
  100. 100. independent dependent occurrent continuant continuant quality processorganism temperature temperature process profile John’s John’s John temperature temperature history
  101. 101. independent dependent occurrent continuant continuant quality processorganism temperature life of an organism John’s John’s John temperature life 102
  102. 102. BFO: The Very Top continuant occurrentindependent dependent continuant continuant quality disposition 103
  103. 103. Disposition- of a glass vase, to shatter if dropped- of a human, to eat- of a banana, to ripen- of John, to lose hair 104
  104. 104. Dispositionif it ceases to exist, then its bearerand/or its immediate surroundingenvironment is physically changedits realization occurs when its bearer is insome special physical circumstancesits realization is what it is in virtue of thebearer’s physical make-up 105
  105. 105. Function- of liver: to store glycogen- of birth canal: to enable transport- of eye: to see- of mitochondrion: to produce ATPfunctions are dispositions which aredesigned or selected for 106 :.
  106. 106. independent dependent occurrent continuant continuant function process eye to see process of seeingJohn’s eye function of John’s John seeing eye: to see 107
  107. 107. OGMS Ontology for General Medical Sciencehttp://code.google.com/p/ogms 108
  108. 108. Physical Disorder 109
  109. 109. Physical Disorder– independent continuant fiat object part A causally linked combination of physical components of the extended organism that is clinically abnormal. 110 :.
  110. 110. Clinically abnormal– (1) not part of the life plan for an organism of the relevant type (unlike aging or pregnancy),– (2) causally linked to an elevated risk either of pain or other feelings of illness, or of death or dysfunction, and– (3) such that the elevated risk exceeds a certain threshold level.**Compare: baldness 111
  111. 111. Big Picture 112
  112. 112. http://code.google.com/p/ogmsDisease =def. – A disposition to undergopathological processes that exists in anorganism because of one or moredisorders in that organism.Disease course =def. – The aggregate ofprocesses in which a disease dispositionis realized. 113
  113. 113. Pathological Process=def. A bodily process that is amanifestation of a disorder and is clinicallyabnormal.Disease =def. – A disposition to undergopathological processes that exists in anorganism because of one or moredisorders in that organism. 114
  114. 114. Cirrhosis - environmental exposure• Etiological process - phenobarbitol-induced hepatic cell death – produces• Disorder - necrotic liver – bears• Disposition (disease) - cirrhosis – realized_in• Pathological process - abnormal tissue repair with cell proliferation and fibrosis that exceed a certain threshold; hypoxia-induced cell death – produces• Abnormal bodily features – recognized_as• Symptoms - fatigue, anorexia• Signs - jaundice, enlarged spleen 115
  115. 115. Influenza - infectious• Etiological process - infection of airway epithelial cells with influenza virus – produces• Disorder - viable cells with influenza virus – bears• Disposition (disease) - flu – realized_in• Pathological process - acute inflammation – produces• Abnormal bodily features – recognized_as• Symptoms - weakness, dizziness• Signs - fever 116
  116. 116. Dispositions and Predispositions All diseases are dispositions; not all dispositions are diseases. Predisposition to Disease =def. – A disposition in an organism that constitutes an increased risk of the organism’s subsequently developing some disease. 117
  117. 117. Huntington’s Disease - genetic• Etiological process - inheritance of  Symptoms & Signs >39 CAG repeats in the HTT gene  used_in – produces  Interpretive process• Disorder - chromosome 4 with  produces abnormal mHTT – bears  Hypothesis - rule out Huntington’s• Disposition (disease) - Huntington’s  suggests disease  Laboratory tests – realized_in  produces• Pathological process - accumulation of mHTT protein fragments, abnormal  Test results - molecular detection of transcription regulation, neuronal cell the HTT gene with >39CAG repeats death in striatum  used_in – produces  Interpretive process• Abnormal bodily features  produces – recognized_as  Result - diagnosis that patient X has a• Symptoms - anxiety, depression disorder that bears the disease• Signs - difficulties in speaking and Huntington’s disease swallowing
  118. 118. HNPCC - genetic pre-disposition• Etiological process - inheritance of a mutant mismatch repair gene – produces• Disorder - chromosome 3 with abnormal hMLH1 – bears• Disposition (disease) - Lynch syndrome – realized_in• Pathological process - abnormal repair of DNA mismatches – produces• Disorder - mutations in proto-oncogenes and tumor suppressor genes with microsatellite repeats (e.g. TGF-beta R2) – bears• Disposition (disease) - non-polyposis colon cancer
  119. 119. Systemic arterial hypertension• Etiological process – abnormal  Symptoms & Signs reabsorption of NaCl by the kidney  used_in – produces  Interpretive process  produces• Disorder – abnormally large scattered molecular aggregate of salt in the  Hypothesis - rule out hypertension blood  suggests – bears  Laboratory tests  produces• Disposition (disease) - hypertension – realized_in  Test results -  used_in• Pathological process – exertion of abnormal pressure against arterial wall  Interpretive process  produces – produces  Result - diagnosis that patient X has a• Abnormal bodily features disorder that bears the disease hypertension – recognized_as• Symptoms -• Signs – elevated blood pressure
  120. 120. Type 2 Diabetes Mellitus• Etiological process –  Symptoms & Signs  used_in – produces• Disorder – abnormal pancreatic beta  Interpretive process  produces cells and abnormal muscle/fat cells – bears  Hypothesis - rule out diabetes mellitus  suggests• Disposition (disease) – diabetes mellitus  Laboratory tests – fasting serum blood glucose, oral glucose challenge test, and/or – realized_in blood hemoglobin A1c• Pathological processes – diminished  produces insulin production , diminished  Test results - muscle/fat uptake of glucose  used_in – produces  Interpretive process• Abnormal bodily features  produces – recognized_as  Result - diagnosis that patient X has a• Symptoms – polydipsia, polyuria, disorder that bears the disease type 2 polyphagia, blurred vision diabetes mellitus• Signs – elevated blood glucose and hemoglobin A1c
  121. 121. Type 1 hypersensitivity to penicillin• Etiological process – sensitizing of mast  Symptoms & Signs cells and basophils during exposure to  used_in penicillin-class substance  Interpretive process – produces  produces• Disorder – mast cells and basophils with  Hypothesis - epitope-specific IgE bound to Fc epsilon  suggests receptor I  Laboratory tests – – bears  produces• Disposition (disease) – type I  Test results – occasionally, skin testing hypersensitivity  used_in – realized_in  Interpretive process•  produces Pathological process – type I hypersensitivity reaction  Result - diagnosis that patient X has a – produces disorder that bears the disease type 1 hypersensitivity to penicillin• Abnormal bodily features – recognized_as• Symptoms – pruritis, shortness of breath• Signs – rash, urticaria, anaphylaxis
  122. 122. Early Onset Alzheimer’s DiseaseDisorder –  mutations in APP, PSEN1 and PSEN2 bearsDisposition – impaired APP processing realized inPathological process – accumulation of intra- and extracellular protein in thebrainproduces Disorder – amyloid plaque and neurofibrillary tanglesbearsDisposition – of neurons to dierealized inPathological process – neuronal loss producesDisorder – cognitive brain regions damaged and reduced in size bearsDisposition (disease) – Alzheimer’s dementia realized inSymptoms – episodic memory loss and other cognitive domain impairment 123
  123. 123. Arterial Aneurysm• Disposition – atherosclerosis – realized in• Pathological process – fatty material collects within the walls of arteries – produces• Disorder – artery with weakened wall – bears• Disposition – of artery to become distended – realized_in• Pathological process – process of distending – produces• Disorder – arterial aneurysm – bears• Disposition – of artery to rupture – realized in• Pathological process – (catastrophic event) of rupturing – produces• Disorder – ruptured artery, arterial system with dangerously low blood pressure – bears• Disposition – circulatory failure – realized in• Pathological process – exsanguination, failure of homeostasis – produces• Death 124
  124. 124. Hemorrhagic stroke• Disorder – cerebral arterial aneurysm – bears• Disposition – of weakened artery to rupture – realized in• Pathological process – rupturing of weakened blood vessel – produces• Disorder – Intraparenchymal cerebral hemorrhage – bears• Disposition (disease) – to increased intra-cranial pressure – realized in• Pathological process – increasing intra-cranial pressure, compression of brain structures – produces• Disorder – Cerebral ischemia, Cerebral neuronal death – bears• Disposition (disease) – stroke – realized in• Symptoms – weakness/paralysis, loss of sensation, etc 125
  125. 125. 126
  126. 126. coronary heart disease early lesions asymptomatic surface unstable stable and small (‘silent’) disruption of angina anginafibrous plaques infarction plaque instantiates instantiates instantiates instantiates instantiates at t1 at t2 at t3 at t4 at t5 John’s coronary heart disease 127 time
  127. 127. independent dependent occurrent continuant continuant disposition process disorder course of disease disease John’s John’sdisordered coronary heart course of John’s heart disease disease 128

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