2. Basic Building Blocks for Biomedical Ontologies Barry Smith 1

3. Problems with UMLS-style approaches let a million ontologies bloom, each one close to the terminological habits of its authors in concordance with the “not invented here” syndrome then map these ontologies, and use these mappings to integrate your different pots of data 2

4. Ontology success stories, and some reasons for failure A fragment of the “Linked Open Data” in the biomedical domain 3

5. What you get with ‘mappings’ HPO: all phenotypes (excess hair loss, duck feet...) 4

6. What you get with ‘mappings’ HPO: all phenotypes (excess hair loss, duck feet...) NCIT: all organisms 5

7. What you get with ‘mappings’ all phenotypes (excess hair loss, duck feet) all organisms allose (a form of sugar) 6

8. 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.) 7

9. Mappings are hard They create an N 2 problem; are fragile, and expensive to maintain Need new authorities to maintain(one for each pair of mapped ontologies), yielding new risk of forking – who will police the mappings? The goal should be to minimize the need for mappings, by avoiding redundancy in the first place – one ontology for each domain Invest resources in disjoint ontology modules which work well together – reduce need for mappings to minimum possible 8

10. 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 serious investment in annotation will be defeated from the start relevant data will not be found, because it will be lost in multiple semantic cemeteries 9

11. 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 used together is small – integration = addition where these ontologies are stable by creating a scenario in which people will find it profitable to reuse ontologies, terminologies and coding systems which have been tried and tested 10

12. Reasons why GO has been successful It is a system for prospective standardization built with coherent top level but with content contributed and monitored by domain specialists Based on community consensus Updated every night Clear versioning principles ensure backwards compatibility; prior annotations do not lose their value Initially low-tech to encourage users, with movement to more powerful formal approaches (including OWL-DL – though still proceeding caution) 11

13. 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 Tracker for user input and help desk with rapid turnaround 12

14. GO has been amazingly successful in overcoming the data balkanization problem but it covers only generic biological entities of three sorts: – cellular components – molecular functions – biological processes no diseases, symptoms, disease biomarkers, protein interactions, experimental processes … 13

15. RELATION TO TIME GRANULARITY CONTINUANTOCCURRENT INDEPENDENTDEPENDENT ORGAN AND ORGANISM Organism (NCBI Taxonomy) Anatomical Entity (FMA, CARO) Organ Function (FMP, CPRO) Phenotypic Quality (PaTO) Biological Process (GO) CELL AND CELLULAR COMPONENT Cell (CL) Cellular Component (FMA, GO) Cellular Function (GO) MOLECULE Molecule (ChEBI, SO, RnaO, PrO) Molecular Function (GO) Molecular Process (GO) OBO (Open Biomedical Ontology) Foundry proposal (Gene Ontology in yellow) 14

16. RELATION TO TIME GRANULARITY CONTINUANTOCCURRENT INDEPENDENTDEPENDENT ORGAN AND ORGANISM Organism (NCBI Taxonomy) Anatomical Entity (FMA, CARO) Organ Function (FMP, CPRO) Phenotypic Quality (PaTO) Biological Process (GO) CELL AND CELLULAR COMPONENT Cell (CL) Cellular Component (FMA, GO) Cellular Function (GO) MOLECULE Molecule (ChEBI, SO, RnaO, PrO) Molecular Function (GO) Molecular Process (GO) Environment Ontology Environment Ontology (ENVO) 15

17. RELATION TO TIME GRANULARITY CONTINUANTOCCURRENT INDEPENDENTDEPENDENT COMPLEX OF ORGANISMS Family, Community, Deme, Population Organ Function (FMP, CPRO) Population Phenotype Population Process ORGAN AND ORGANISM Organism (NCBI Taxonomy) Anatomical Entity (FMA, CARO) Phenotypic Quality (PaTO) Biological Process (GO) CELL AND CELLULAR COMPONENT Cell (CL) Cellular Component (FMA, GO) Cellular Function (GO) MOLECULE Molecule (ChEBI, SO, RnaO, PrO) Molecular Function (GO) Molecular Process (GO) Population-level ontologies 16

18.  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 The OBO Foundry: a step-by-step, evidence-based approach to expanding the GO 17

19. OBO Foundry Principles  Common governance (coordinating editors)  Common training  Common architecture: simple shared top level ontology (BFO) shared Relation Ontology: www.obofoundry.org/ro 18

20. 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 19

21. Principles http://obofoundry.org/wiki/index.php/OBO_Foundry Principles 20

22. CONTINUANTOCCURRENT INDEPENDENTDEPENDENT ORGAN AND ORGANISM Organism (NCBI Taxonomy) Anatomical Entity (FMA, CARO) Organ Function (FMP, CPRO) Phenotypic Quality (PaTO) Organism-Level Process (GO) CELL AND CELLULAR COMPONENT Cell (CL) Cellular Component (FMA, GO) Cellular Function (GO) Cellular Process (GO) MOLECULE Molecule (ChEBI, SO, RnaO, PrO) Molecular Function (GO) Molecular Process (GO) OBO Foundry coverage GRANULARITY RELATION TO TIME 21

23. ORTHOGONALITY modularity 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 22

24. Benefits of coordination Can more easily reuse what is made by others Can more easily inspect and criticize what is made by others Leads to innovations (e.g. Mireot strategy for importing terms into ontologies) 23

25. RELATION TO TIME GRANULARITY CONTINUANTOCCURRENT INDEPENDENTDEPENDENT ORGAN AND ORGANISM Organism (NCBI Taxonomy) Anatomical Entity (FMA, CARO) Organ Function (FMP, CPRO) Phenotypic Quality (PaTO) Biological Process (GO) XAOZFA CELL AND CELLULAR COMPONENT Cell (CL) Cellular Component (FMA, GO) Cellular Function (GO) MOLECULE Molecule (SO, RnaO) Molecular Function (GO) Molecular Process (GO) ChEBIPRO Current Foundry members in yellow 24

26. Foundry ontologies currently under review Plant Ontology (PO) Ontology for Biomedical Investigations (OBI) Ontology for General Medical Science (OBMS) Infectious Disease Ontology (IDO) 25

27. Anatomy Ontology (FMA*, CARO) Environment Ontology (EnvO) Infectious Disease Ontology (IDO*) Biological Process Ontology (GO*) Cell Ontology (CL) Cellular Component Ontology (FMA*, GO*) Phenotypic Quality Ontology (PaTO) Subcellular Anatomy Ontology (SAO) Sequence Ontology (SO*) Molecular Function (GO*) Protein Ontology (PRO*) OBO Foundry Modular Organization top level mid-level domain level Information Artifact Ontology (IAO) Ontology for Biomedical Investigations (OBI) Ontology of General Medical Science (OGMS) Basic Formal Ontology (BFO) 26

28. OBI The Ontology for Biomedical Investigations hfp://purl.org/obo/OBI_0000225 27

29. Purpose of OBI To provide a resource for the unambiguous description of the components of biomedical investigations such as the design, protocols and instrumentation, material, data and types of analysis and statistical tools applied to the data  NOT designed to model biology 28

30. OBI Collaborating Communities Crop sciences Generation Challenge Programme (GCP), Environmental genomics MGED RSBI Group, www.mged.org/Workgroups/rsbi Genomic Standards Consortium (GSC), www.genomics.ceh.ac.uk/genomecatalogue HUPO Proteomics Standards Initiative (PSI), psidev.sourceforge.net Immunology Database and Analysis Portal, www.immport.org Immune Epitope Database and Analysis Resource (IEDB), http://www.immuneepitope.org/home.do International Society for Analytical Cytology, http://www.isac-net.org/ Metabolomics Standards Initiative (MSI), Neurogenetics, Biomedical Informatics Research Network (BIRN), Nutrigenomics MGED RSBI Group, www.mged.org/Workgroups/rsbi Polymorphism Toxicogenomics MGED RSBI Group, www.mged.org/Workgroups/rsbi Transcriptomics MGED Ontology Group 29

31. 30

32. 31

33. 32

34. 33

35. Ontology for General Medical Science http://code.google.com/p/ogms/ (OBO) http://purl.obolibrary.org/obo/ogms.obo (OWL) http://purl.obolibrary.org/obo/ogms.owl 34

36. OGMS-based initiatives Vital Signs Ontology (VSO) (Welch Allyn) EHR / Demographics Ontology Infectious Disease Ontology Mental Health Ontology Emotion Ontology 35

37. Ontology for General Medical Science Jobst Landgrebe (then Co-Chair of the HL7 Vocabulary Group): “the best ontology effort in the whole biomedical domain by far” 36

38. EXPERIMENTAL ARTIFACTS Ontology for Biomedical Investigations (OBI) CLINICAL MEDICINE Ontology of General Medical Science (OGMS) INFORMATION ARTIFACTS Information Artifact Ontology (IAO) How to keep clear about the distinction processes of observation, results of such processes (measurement data) the entities observed 37

39. How is the OBO Foundry organized? Top-Level: Basic Formal Ontology (BFO) Mid-Level: IAO, OBI, OGMS... Domain-Level: Foundry Bio-Ontologies 38

40. Anatomy Ontology (FMA*, CARO) Environment Ontology (EnvO) Infectious Disease Ontology (IDO*) Biological Process Ontology (GO*) Cell Ontology (CL) Cellular Component Ontology (FMA*, GO*) Phenotypic Quality Ontology (PaTO) Subcellular Anatomy Ontology (SAO) Sequence Ontology (SO*) Molecular Function (GO*) Protein Ontology (PRO*) OBO Foundry Modular Organization top level mid-level domain level Information Artifact Ontology (IAO) Ontology for Biomedical Investigations (OBI) Ontology of General Medical Science (OGMS) Basic Formal Ontology (BFO) 39

41. BFO: the very top Continuant Occurrent (Process, Event) Independent Continuant Dependent Continuant 40

42. RELATION TO TIME GRANULARITY CONTINUANTOCCURRENT INDEPENDENTDEPENDENT ORGAN AND ORGANISM Organism (NCBI Taxonomy) Anatomical Entity (FMA, CARO) Organ Function (FMP, CPRO) Phenotypic Quality (PaTO) Biological Process (GO) CELL AND CELLULAR COMPONENT Cell (CL) Cellular Component (FMA, GO) Cellular Function (GO) MOLECULE Molecule (ChEBI, SO, RnaO, PrO) Molecular Function (GO) Molecular Process (GO) 41

43. CONTINUANTOCCURRENT INDEPENDENTDEPENDENT ORGAN AND ORGANISM Organism (NCBI Taxonomy) Anatomical Entity (FMA, CARO) Organ Function (FMP, CPRO) Phenotypic Quality (PaTO) Organism-Level Process (GO) CELL AND CELLULAR COMPONENT Cell (CL) Cellular Component (FMA, GO) Cellular Function (GO) Cellular Process (GO) MOLECULE Molecule (ChEBI, SO, RnaO, PrO) Molecular Function (GO) Molecular Process (GO) obofoundry.org GRANULARITY RELATION TO TIME 42

44. BFO & GO continuant occurrent biological processes independent continuant cellular component dependent continuant molecular function 43

45. Basic Formal Ontology Continuant Occurrent process, event Independent Continuant thing Dependent Continuant quality................ types instances 44

46. Experience with BFO in building ontologies provides a community of skilled ontology developers and users (user group has 120 members) associated logical tools documentation for different types of users a methodology for building conformant ontologies by starting with BFO and populating downwards 45

47. Example: The Cell Ontology

48. How to build an ontology import BFO into ontology editor such as Protégé work with domain experts to create an initial mid- level classification find ~50 most commonly used terms corresponding to types in reality arrange these terms into an informal is_a hierarchy according to this universality principle A is_a B  every instance of A is an instance of B fill in missing terms to give a complete hierarchy (leave it to domain experts to populate the lower levels of the hierarchy) 47

49. The Road to Convergence All ontologies for each given domain (biology, physics, Army operations …) should be part of a single suite of interoperable ontologies should use a common top-level core should require acceptance of common, tested guidelines and common training and governance from all subscribing ontology developers 48

50. :. Users of BFO PharmaOntology (W3C HCLS SIG) MediCognos / Microsoft Healthvault Cleveland Clinic Semantic Database in Cardiothoracic Surgery Major Histocompatibility Complex (MHC) Ontology (NIAID) Neuroscience Information Framework Standard (NIFSTD) and Constituent Ontologies Interdisciplinary Prostate Ontology (IPO) Nanoparticle Ontology (NPO): Ontology for Cancer Nanotechnology Research Neural Electromagnetic Ontologies (NEMO) ChemAxiom – Ontology for Chemistry 49

51. :. Users of BFO GO Gene Ontology CL Cell Ontology SO Sequence Ontology ChEBI Chemical Ontology PATO Phenotype (Quality) Ontology FMA Foundational Model of Anatomy Ontology ChEBI Chemical Entities of Biological Interest PRO Protein Ontology Plant Ontology Environment Ontology Ontology for Biomedical Investigations RNA Ontology 50

52. :. Users of BFO Ontology 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 Ontology US Army Command and Control Ontology Sleep Domain Ontology Subcellular Anatomy Ontology (SAO) Translaftional Medicine On (VO) Yeast Ontology (yOWL) Zebrafish Anatomical Ontology (ZAO) 51

53. :. DOLCE, SUMO, Cyc DOLCE: (Largely) extends BFO, but built to support ‘linguistic and cognitive engineering’ SUMO: No dependent continuants (so: no diabetes, no temperature instances); SUMO has its own tiny biology (‘body- covering’, ‘fruit-Or-vegetable’) 52

54. :. Cyc:ConceivingSomething_BiologicalReproduct ionEvent =def a collection of events; a sub- collection of BiologicalReproductionEvent. In each conceivingSomething_BiologicalReproduction Event, someone becomes pregnant. Cyc:The immaculate conception =def. The ConceivingSomething_BiologicalReproductionEvent in which Mary_MotherOfJesus was conceived. Catholic dogma holds that Mary (unlike Jesus) was conceived by conventional biological means, but that GodOfAbrahamIsaacAndJacob interceded at the time of her conception to keep her free from the stain of original sin, or ‘immaculate’. 53

55. Basic Formal Ontology continuant occurrent independent continuant dependent continuant organism 54

56. 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... 55

57. Occurrents processes, events, happenings –your life –this process of accelerated cell division 56

58. Qualities temperature blood pressure mass... are continuants they exist through time while undergoing changes 57

59. Qualities temperature / 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 58

60. A Chart representing how John’s temperature changes 59

61. A Chart representing how John’s temperature changes 60

62. John’s temperature, the temperature he has throughout his entire life, cycles through different determinate temperatures from one time to the next John’s temperature is a physiology variable which, in thus changing, exerts an influence on other physiology variables through time 61

63. BFO: The Very Top continuant independent continuant dependent continuant quality occurrent temperature 62

64. Blinding Flash of the Obvious independent continuant dependent continuant quality temperature types instances organism John John’s temperature 63

65. Blinding Flash of the Obvious independent continuant dependent continuant quality temperature types instances organism John John’s temperature 64

66. Blinding Flash of the Obvious temperature types instances organism John John’s temperature. inheres_in 65

67. temperature types instances John’s temperature 37ºC37.1ºC37.5ºC37.2ºC37.3ºC37.4ºC instantiates at t 1 instantiates at t 2 instantiates at t 3 instantiates at t 4 instantiates at t 5 instantiates at t 6 66

68. human types instances John embryofetusadultneonateinfantchild instantiates at t 1 instantiates at t 2 instantiates at t 3 instantiates at t 4 instantiates at t 5 instantiates at t 6 67

69. Temperature subtypes Development-stage subtypes are threshold divisions (hence we do not have sharp boundaries, and we have a certain degree of choice, e.g. in how many subtypes to distinguish, though not in their ordering) 68

70. independent continuant dependent continuant quality temperature types instances organism John John’s temperature 69

71. independent continuant dependent continuant quality temperature organism John John’s temperature occurrent process course of temperature changes John’s temperature history 70

72. independent continuant dependent continuant quality temperature organism John John’s temperature occurrent process life of an organism John’s life 71

73. BFO: The Very Top continuantoccurrent independent continuant dependent continuant qualitydisposition 72

74. BFO: The Very Top continuant independent continuant dependent continuant quality function role disposition occurrent 73

75. disposition - of a glass vase, to shatter if dropped - of a human, to eat - of a banana, to ripen - of John, to lose hair 74

76. disposition if it ceases to exist, then its bearer and/or its immediate surrounding environment is physically changed its realization occurs when its bearer is in some special physical circumstances its realization is what it is in virtue of the bearer’s physical make-up 75

77. function - of liver: to store glycogen - of birth canal: to enable transport - of eye: to see - of mitochondrion: to produce ATP not optional; reflection of physical makeup of bearer 76

78. role optional: exists because the bearer is in some special natural, social, or institutional set of circumstances in which the bearer does not have to be 77

79. role - bearers can have more than one role person as student and staff member - roles often form systems of mutual dependence husband / wife first in queue / last in queue doctor / patient host / pathogen 78

80. role of some chemical compound: to serve as analyte in an experiment of a dose of penicillin in this human child: to treat a disease of this bacteria in a primary host: to cause infection 79

81. independent continuant dependent continuant function to see eye John’s eye function of John’s eye: to see occurrent process process of seeing John seeing 80

82. New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U Particulars and Universals methis walking my left leg this leg moving to make me walk human being living creature walkingleg moving leg function process Instance-of at t Instance-of at t Instance-of at t Instance-of 1 81

83. New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U instanceOf at t 2 instanceOf at t 1 instanceOf at t 2 The importance of temporal indexing #1’s stomach benign tumor instanceOf at t 1 #4 malignant tumor partOf at t 1 stomach partOf at t 2 82

84. New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U Continuants and Occurrents methis walking my left leg this leg moving to make me walk human being living creature walkingleg moving leg function process Instance-of at t Instance-of at t Instance-of at t Instance-of 2 83

85. New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U Independent versus dependent Independent entities Do not require any other entity to exist to enable their own existence Dependent entities Require the existence of some other entity for their existence methis walking my left leg this leg moving to make me walk Independent continuants Dependent continuants Occurrents (are all dependent) 3 84

86. New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U Dependent continuants Realized –Quality:redness (of blood) Realizable –Function:to flex (of knee joint) –Role:student –Power:boss –Disposition:brittleness (of a bone) Realizations flexing studying ordering breaking continuantsoccurrents 3 85

87. New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U Relation Ontology Continuant Occurrent process, event Independent Continuant ~ thing Dependent Continuant................ universals particulars has_participant inheres_in instance_of (at t) isa 86

88. New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U tt t instanceOf The essential pieces material object spacetime region me some temporal region my life my 4D STR some spatial region course spatial region temporal region dependent continuant some quality located-in at t at t participantOf at toccupies projectsOn projectsOn at t 87

89. OGMS Ontology for General Medical Science http://code.google.com/p/ogms 88

90. New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U ontology for the representation of –diseases, signs, symptoms –clinical processes –diagnosis, treatment and outcomes fundamental idea: –a disease is a disposition rooted in some (physical) disorder in the organism Ontology of General Medical Science (OGMS) 89

91. New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U Motivation Clarity about: –disease etiology and progression –disease and the diagnostic process –phenotype and signs/symptoms –entities in reality and observations of sucn entities 90

92. Physical Disorder 91

93. :. Physical Disorder – independent continuant fiat object part A causally linked combination of physical components of the extended organism that is clinically abnormal. 92

94. 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 93

95. Big Picture 94

96. Pathological Process =def. A bodily process that is a manifestation of a disorder and is clinically abnormal. Disease =def. – A disposition to undergo pathological processes that exists in an organism because of one or more disorders in that organism. 95

97. 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 96

98. 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. 97

99. 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 –realized in Symptoms (including pain) 98

100. Huntington’s Disease - genetic Etiological process - inheritance of >39 CAG repeats in the HTT gene – produces Disorder - chromosome 4 with abnormal mHTT – bears Disposition (disease) - Huntington’s disease – realized_in Pathological process - accumulation of mHTT protein fragments, abnormal transcription regulation, neuronal cell death in striatum – produces Abnormal bodily features – recognized_as Symptoms - anxiety, depression Signs - difficulties in speaking and swallowing Symptoms & Signs used_in Interpretive process produces Hypothesis - rule out Huntington’s suggests Laboratory tests produces Test results - molecular detection of the HTT gene with >39CAG repeats used_in Interpretive process produces Result - diagnosis that patient X has a disorder that bears the disease Huntington’s disease 99

101. 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 100

102. 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, splenomegaly Symptoms & Signs used_in Interpretive process produces Hypothesis - rule out cirrhosis suggests Laboratory tests produces Test results - elevated liver enzymes in serum used_in Interpretive process produces Result - diagnosis that patient X has a disorder that bears the disease cirrhosis 101

103. Systemic arterial hypertension Etiological process – abnormal reabsorption of NaCl by the kidney –produces Disorder – abnormally large scattered molecular aggregate of salt in the blood –bears Disposition (disease) - hypertension –realized_in Pathological process – exertion of abnormal pressure against arterial wall –produces Abnormal bodily features –recognized_as Symptoms - headaches, dizziness Signs – elevated blood pressure Symptoms & Signs used_in Interpretive process produces Hypothesis - rule out hypertension suggests Laboratory tests produces Test results - used_in Interpretive process produces Result - diagnosis that patient X has a disorder that bears the disease hypertension 102

104. Type 2 Diabetes Mellitus Etiological process – –produces Disorder – abnormal pancreatic beta cells and abnormal muscle/fat cells –bears Disposition (disease) – diabetes mellitus –realized_in Pathological processes – diminished insulin production, diminished muscle/fat uptake of glucose –produces Abnormal bodily features –recognized_as Symptoms – polydipsia, polyuria, polyphagia, blurred vision Signs – elevated blood glucose and hemoglobin A1c Symptoms & Signs used_in Interpretive process produces Hypothesis - rule out diabetes mellitus suggests Laboratory tests – fasting serum blood glucose, oral glucose challenge test, and/or blood hemoglobin A1c produces Test results - used_in Interpretive process produces Result - diagnosis that patient X has a disorder that bears the disease type 2 diabetes mellitus 103

105. Type 1 hypersensitivity to penicillin Etiological process – sensitizing of mast cells and basophils during exposure to penicillin-class substance –produces Disorder – mast cells and basophils with epitope-specific IgE bound to Fc epsilon receptor I –bears Disposition (disease) – type I hypersensitivity –realized_in Pathological process – type I hypersensitivity reaction –produces Abnormal bodily features –recognized_as Symptoms – pruritis, shortness of breath Signs – rash, urticaria, anaphylaxis Symptoms & Signs used_in Interpretive process produces Hypothesis - suggests Laboratory tests – produces Test results – occasionally, skin testing used_in Interpretive process produces Result - diagnosis that patient X has a disorder that bears the disease type 1 hypersensitivity to penicillin 104

106. 105

107. Disease vs. Disease course Disease =def. – A disposition to undergo pathological processes that exists in an organism because of one or more disorders in that organism. Disease course =def. – The aggregate of processes in which a disease disposition is realized. 106

108. coronary heart disease John’s coronary heart disease disease … asymptomatic (‘silent’) infarction disease at the stage where it is associated early lesions and small fibrous plaques stable angina disease …. surface disruption of plaque unstable angina instantiates at t 1 instantiates at t 2 instantiates at t 3 instantiates at t 4 instantiates at t 5 time 107

109. independent continuant dependent continuant disposition disease disorder John’s disordered heart John’s coronary heart disease occurrent process course of disease course of John’s disease 108

110. OGMSIDO Independent Continuant Disorder Infectious disorder Dependent Continuant Disease Predisposition to disease Infectious disease Protective resistance OccurrentDisease course Infectious disease course Examples of ontology terms

111. IDO (Infectious Disease Ontology) Core Follows GO strategy of providing a canonical ontology of what is involved in every infectious disease – host, pathogen, vector, virulence, vaccine, transmission – accompanied by IDO Extensions for specific diseases, pathogens and vectors Provides common terminology resources and tested common guidelines for a vast array of different disease communities 110

112. Infectious Disease Ontology Consortium MITRE, Mount Sinai, UTSouthwestern – Influenza IMBB/VectorBase – Vector borne diseases (A. gambiae, A. aegypti, I. scapularis, C. pipiens, P. humanus) Colorado State University – Dengue Fever Duke University – Tuberculosis, Staph. aureus Cleveland Clinic – Infective Endocarditis University of Michigan – Brucilosis Duke University, University at Buffalo – HIV 111

113. 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 112

114. Influenza – disease course 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 113 The disorder also induces normal physiological processes (immune response) that can results in the elimination of the disorder (transient disease course).

115. Big Picture 114