The National Center for Biomedical Ontology Stanford Berkeley

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The National Center for Biomedical Ontology Stanford – Berkeley Mayo – Victoria – Buffalo

The National Center for Biomedical Ontology Stanford – Berkeley Mayo – Victoria – Buffalo UCSF – Oregon – Cambridge

Ontologies are essential to make sense of biomedical data

Ontologies are essential to make sense of biomedical data

A biological ontology is: § A machine interpretable representation of some aspect of biological

A biological ontology is: § A machine interpretable representation of some aspect of biological reality § what kinds of things exist? § what are the relationships between these things? eye disc develops from sense organ is_a eye part_of ommatidium

The Foundational Model of Anatomy

The Foundational Model of Anatomy

Knowledge workers seem trapped in a pre-industrial age § Most ontologies are § Of

Knowledge workers seem trapped in a pre-industrial age § Most ontologies are § Of relatively small scale § Built by small groups working arduously in isolation § Success rests heavily on the particular talents of individual artisans, rather than on SOPs and best practices § There are few technologies available to make this process “faster, better, cheaper”

A Portion of the OBO Library

A Portion of the OBO Library

National Center for Biomedical Ontology Capture and index experimental results Open Biomedical Ontologies (OBO)

National Center for Biomedical Ontology Capture and index experimental results Open Biomedical Ontologies (OBO) Revise biomedical understanding Open Biomedical Data (OBD) Bio. Portal Relate experimental data to results from other sources

§ Stanford: Tools for ontology alignment, indexing, and management (Cores 1, 4– 7: Mark

§ Stanford: Tools for ontology alignment, indexing, and management (Cores 1, 4– 7: Mark Musen) § Lawrence–Berkeley Labs: Tools to use ontologies for data annotation (Cores 2, 5– 7: Suzanna Lewis) § Mayo Clinic: Tools for access to large controlled terminologies (Core 1: Chris Chute) § Victoria: Tools for ontology and data visualization (Cores 1 and 2: Margaret-Anne Story) § University at Buffalo: Dissemination of best practices for ontology engineering (Core 6: Barry Smith)

c. Bio Driving Biological Projects § Trial Bank: UCSF, Ida Sim § Flybase: Cambridge,

c. Bio Driving Biological Projects § Trial Bank: UCSF, Ida Sim § Flybase: Cambridge, Michael Ashburner § ZFIN: Oregon, Monte Westerfield

The National Center for Biomedical Ontology Core 3: Driving Biological Projects Monte Westerfield

The National Center for Biomedical Ontology Core 3: Driving Biological Projects Monte Westerfield

Animal disease models Animal models Mutant Gene Mutant or missing Protein Mutant Phenotype

Animal disease models Animal models Mutant Gene Mutant or missing Protein Mutant Phenotype

Animal disease models Humans Animal models Mutant Gene Mutant or missing Protein Mutant Phenotype

Animal disease models Humans Animal models Mutant Gene Mutant or missing Protein Mutant Phenotype (disease) Mutant Phenotype (disease model)

Animal disease models Humans Animal models Mutant Gene Mutant or missing Protein Mutant Phenotype

Animal disease models Humans Animal models Mutant Gene Mutant or missing Protein Mutant Phenotype (disease) Mutant Phenotype (disease model)

Animal disease models Humans Animal models Mutant Gene Mutant or missing Protein Mutant Phenotype

Animal disease models Humans Animal models Mutant Gene Mutant or missing Protein Mutant Phenotype (disease) Mutant Phenotype (disease model)

SHH-/+ SHH-/- shh-/+ shh-/-

SHH-/+ SHH-/- shh-/+ shh-/-

Phenotype (clinical sign) = entity + attribute

Phenotype (clinical sign) = entity + attribute

Phenotype (clinical sign) = entity P 1 = eye + attribute + hypoteloric

Phenotype (clinical sign) = entity P 1 = eye + attribute + hypoteloric

Phenotype (clinical sign) = entity P 1 P 2 = eye = midface +

Phenotype (clinical sign) = entity P 1 P 2 = eye = midface + attribute + hypoteloric + hypoplastic

Phenotype (clinical sign) = entity P 1 P 2 P 3 = eye =

Phenotype (clinical sign) = entity P 1 P 2 P 3 = eye = midface = kidney + + attribute hypoteloric hypoplastic hypertrophied

Phenotype (clinical sign) = entity P 1 P 2 P 3 = eye =

Phenotype (clinical sign) = entity P 1 P 2 P 3 = eye = midface = kidney + + ZFIN: eye midface kidney attribute hypoteloric hypoplastic hypertrophied PATO: hypoteloric + hypoplastic hypertrophied

Phenotype (clinical sign) = entity + attribute Anatomy ontology Cell & tissue ontology Developmental

Phenotype (clinical sign) = entity + attribute Anatomy ontology Cell & tissue ontology Developmental ontology Gene ontology biological process molecular function cellular component + PATO (phenotype and trait ontology)

Phenotype (clinical sign) = entity P 1 P 2 P 3 = eye =

Phenotype (clinical sign) = entity P 1 P 2 P 3 = eye = midface = kidney + + attribute hypoteloric hypoplastic hypertrophied Syndrome = P 1 + P 2 + P 3 (disease) = holoprosencephaly

Human holoprosencephaly Zebrafish shh Zebrafish oep

Human holoprosencephaly Zebrafish shh Zebrafish oep

Human holoprosencephaly Zebrafish shh Zebrafish oep

Human holoprosencephaly Zebrafish shh Zebrafish oep

ZFIN mutant genes

ZFIN mutant genes

OMIM genes ZFIN mutant genes

OMIM genes ZFIN mutant genes

OMIM genes ZFIN mutant genes Fly. Base mutant genes

OMIM genes ZFIN mutant genes Fly. Base mutant genes

OMIM gene ZFIN gene LAMB 1 lamb 1 FECH Fly. Base gene Fly. Base

OMIM gene ZFIN gene LAMB 1 lamb 1 FECH Fly. Base gene Fly. Base mut pub ZFIN mut pub Lan. B 1 5 15 fech Ferrochelatase 2 5 GLI 2 gli 2 a ci 388 SLC 4 A 1 slc 4 a 1 CG 8177 MYO 7 A myo 7 a ALAS 2 mouse rat SNO MED OMIM disease 39 - 29 Protoporphyria, Erythropoietic 41 22 - 7 7 19 Renal Tubular Acidosis, RTADR ck 84 5 16 Deafness; DFNB 2; DFNA 11 alas 2 Alas 1 7 14 Anemia, Sideroblastic, XLinked KCNH 2 kcnh 2 sei 27 3 12 - MYH 6 myh 6 Mhc 166 3 1 12 Cardiomyopathy, Familial Hypertrophic; CMH TP 53 tp 53 64 3 3 19 11 Breast Cancer ATP 2 A 1 atp 2 a 1 Ca-P 60 A 32 6 1 11 Brody Myopathy EYA 1 eya 251 5 4 6 Branchiootorenal Dysplasia SOX 10 sox 10 Sox 100 B 1 17 4 4 Waardenburg-Shah Syndrome 2 9 3

National Center for Biomedical Ontology Capture and index experimental results Open Biomedical Ontologies (OBO)

National Center for Biomedical Ontology Capture and index experimental results Open Biomedical Ontologies (OBO) Revise biomedical understanding Open Biomedical Data (OBD) Bio. Portal Relate experimental data to results from other sources

The National Center for Biomedical Ontology Core 2: Bioinformatics Suzanna Lewis

The National Center for Biomedical Ontology Core 2: Bioinformatics Suzanna Lewis

c. Bioinformatics Goals 1. Apply ontologies § Software toolkit for annotation 2. Manage data

c. Bioinformatics Goals 1. Apply ontologies § Software toolkit for annotation 2. Manage data § Databases and interfaces to store and view annotations 3. Investigate and compare § Linking human diseases to genetic models 4. Maintain § Ongoing reconciliation of ontologies with annotations

c. Bioinformatics Goals 1. Apply ontologies § Software toolkit for annotation 2. Manage data

c. Bioinformatics Goals 1. Apply ontologies § Software toolkit for annotation 2. Manage data § Databases and interfaces to store and view annotations 3. Investigate and compare § Linking human diseases to genetic models 4. Maintain § Ongoing reconciliation of ontologies with annotations

Phenotype as an observation context The class of thing observed environment evidence publication figures

Phenotype as an observation context The class of thing observed environment evidence publication figures assay genetic sequence ID ontology

Phenotype from published evidence

Phenotype from published evidence

Ontologies enable users to describe assays

Ontologies enable users to describe assays

Phenotype as an observation context The class of thing observed environment evidence publication figures

Phenotype as an observation context The class of thing observed environment evidence publication figures assay genetic sequence ID ontology

Ontologies enable users to describe environments

Ontologies enable users to describe environments

Phenotype as an observation context The class of thing observed environment evidence publication figures

Phenotype as an observation context The class of thing observed environment evidence publication figures assay genetic sequence ID ontology

Ontologies enable users to describe genotypes

Ontologies enable users to describe genotypes

National Center for Biomedical Ontology Capture and index experimental results Open Biomedical Ontologies (OBO)

National Center for Biomedical Ontology Capture and index experimental results Open Biomedical Ontologies (OBO) Revise biomedical understanding Open Biomedical Data (OBD) Bio. Portal Relate experimental data to results from other sources

The National Center for Biomedical Ontology Core 1: Computer Science Mark Musen

The National Center for Biomedical Ontology Core 1: Computer Science Mark Musen

E-science needs technologies § To help build and extend ontologies § To locate ontologies

E-science needs technologies § To help build and extend ontologies § To locate ontologies and to relate them to one another § To visualize relationships and to aid understanding § To facilitate evaluation and annotation of ontologies

Ontology engineering requires management of complexity § How can we § keep track of

Ontology engineering requires management of complexity § How can we § keep track of hundreds of relationships? § understand the implications of changes to a large ontology? § know where ontologies are underspecified? And where they are over constrained?

E-science needs technologies § To help build and extend ontologies § To locate ontologies

E-science needs technologies § To help build and extend ontologies § To locate ontologies and to relate them to one another § To visualize relationships and to aid understanding § To facilitate evaluation and annotation of ontologies

Core 1 Components

Core 1 Components

National Center for Biomedical Ontology Capture and index experimental results Open Biomedical Ontologies (OBO)

National Center for Biomedical Ontology Capture and index experimental results Open Biomedical Ontologies (OBO) Revise biomedical understanding Open Biomedical Data (OBD) Bio. Portal Relate experimental data to results from other sources

Core 4: Infrastructure § Builds on existing IT infrastructure at Stanford and at our

Core 4: Infrastructure § Builds on existing IT infrastructure at Stanford and at our collaborating institutions § Adds § Online resources and technical support for the user community § Collaboration tools to link all participating sites

Core 5: Education and Training § Builds on existing, strong informatics training programs at

Core 5: Education and Training § Builds on existing, strong informatics training programs at Stanford, Berkeley, UCSF, Mayo/Minnesota, and Buffalo § New postdoctoral positions at Stanford, Berkeley, and Buffalo § New visiting scholars program

Core 6: Dissemination § Active relationships with relevant professional societies and agencies (e. g.

Core 6: Dissemination § Active relationships with relevant professional societies and agencies (e. g. , HL 7, IEEE, WHO, NIH) § Internet-based resources for discussing, critiquing, and annotating ontologies in OBO § Cooperation with other NCBCs to offer a library of open-source software tools § Training workshops to aid biomedical scientists in ontology development

Upcoming c. Bio Dissemination Workshops § Image Ontology Workshop Stanford CA, March 24– 25,

Upcoming c. Bio Dissemination Workshops § Image Ontology Workshop Stanford CA, March 24– 25, 2006 § Training in Biomedical Ontology Schloss Dagstuhl, May 21– 24, 2006 § Training in Biomedical Ontology Baltimore, November 6– 8, 2006 (in association with FOIS and AMIA conferences)

Core 7: Administration § Project management shared between Stanford and Berkeley § Executive committee

Core 7: Administration § Project management shared between Stanford and Berkeley § Executive committee (PI, co-PI, Center director, and Center associate director) provides day-to-day management and oversight § Council (All site PIs, including PIs of DBPs) provides guidance and coordination of work plans § Each Core has a designated “lead” selected from the Council

c. Bi. O Organization Chart Other NCBC Centers NIH Program Officer PI Mark Musen

c. Bi. O Organization Chart Other NCBC Centers NIH Program Officer PI Mark Musen Biomedical Science and Community Science Officers Co-PI Suzanna Lewis Center Director Daniel Rubin Associate Director Sima Misra Scientific Advisory Committee Executive Committee Musen, Lewis, Rubin, Misra Business Manager Rosalind Ravasio c. BIO Council Musen, Lewis, Rubin, Misra, Smith, Storey, Chute, Ashburner, Westerfield, Sim Administrative Asst. Donna Mahood Core 1 Lead Mark Musen Biomedical Computing Community Core 2 Lead Suzanna Lewis Core 3 Lead Exec Committee Core 4 Lead Daniel Rubin Core 5 Lead Mark Musen Core 6 Lead Barry Smith

Ontologies are essential to make sense of biomedical data

Ontologies are essential to make sense of biomedical data