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Systems biology is an approach to biology that emphasizes thestructure and dynamic behavior of biological systems and theinteractions that occur within them. To succeed, systems biologycrucially depends on the accessibility and integration of data acrossdomains and levels of granularity. Biomedical ontologies weredeveloped to facilitate such an integration for data and are oftenused to annotate biosimulation models in systems biology.Here, I present an approach towards combining both disciplines in a common framework that enables information to flow between both.
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Towards integration of systems biology and biomedicalontologies
Robert Hoehndorf
Department of GeneticsUniversity of Cambridge
29 March 2011
Robert Hoehndorf (University of Cambridge) Harvesting SBML 29 March 2011 1 / 28
Introduction Motivation
Motivation
Robert Hoehndorf (University of Cambridge) Harvesting SBML 29 March 2011 2 / 28
Introduction Motivation
Motivation
Robert Hoehndorf (University of Cambridge) Harvesting SBML 29 March 2011 3 / 28
Introduction Ontology
Applied ontology
ontology (philosophy) studies the nature of existence and categoriesof being
an ontology (computer science) is the “explicit specification of aconceptualization of a domain” [Gruber, 1993]
ontologies specify the meaning of terms in a vocabulary
formalized ontologies can be used by computers and automatedsystems
Applied ontology is the branch of knowledge representation that focuseson the content.
Robert Hoehndorf (University of Cambridge) Harvesting SBML 29 March 2011 4 / 28
Introduction Ontology
Open Biomedical Ontologies (OBO)
Body
Organ
Cell
Molecule
Tissue
Population
Gene
Transcript
Organelle
Individual
Physical object Quality Function Process
Gene OntologyCelltype
Sequence Ontology
GO-CC
ChEBI Ontology
AnatomyOntology
PhenotypeOntology
Robert Hoehndorf (University of Cambridge) Harvesting SBML 29 March 2011 5 / 28
Introduction Ontology
Systems biology
Systems biology...is about putting together rather than takingapart, integration rather than reduction. [Denis Noble]
multi-scale data integration
domains and levels of granularityspecieskinds of data
integration of in silico, in vitro and in vivo research
focus on emergent properties
simulation of biological systems
predict and simulate systems’ behavior
Robert Hoehndorf (University of Cambridge) Harvesting SBML 29 March 2011 6 / 28
Introduction Ontology
Systems biologyChallenges (Kitano, 2002)
data integration
validation
standard languages
specificationexchangeresults
Can we use ontologies to address these problems?
Robert Hoehndorf (University of Cambridge) Harvesting SBML 29 March 2011 7 / 28
Introduction Ontology
Systems biologyChallenges (Kitano, 2002)
data integration
validation
standard languages
specificationexchangeresults
Can we use ontologies to address these problems?
Robert Hoehndorf (University of Cambridge) Harvesting SBML 29 March 2011 7 / 28
Harvesting SBML
MIRIAM annotationsAnnotation of SBML
Robert Hoehndorf (University of Cambridge) Harvesting SBML 29 March 2011 8 / 28
Harvesting SBML
MIRIAM annotationsAnnotation of SBML
MIRIAM provides annotation of SBML entities
ontologies are treated as meta-data
searchsemantic similaritydocumentation
no integration with modelling language
Robert Hoehndorf (University of Cambridge) Harvesting SBML 29 March 2011 9 / 28
Harvesting SBML
MIRIAM annotationsInformation flow hypothesis
Integration of SBML and ontologies could lead to information flowbetween models and ontologies.
Information flow enables the use of ontologies for
verification,
access to data,
integration and combination of models.
Robert Hoehndorf (University of Cambridge) Harvesting SBML 29 March 2011 10 / 28
Harvesting SBML
MIRIAM annotations
Robert Hoehndorf (University of Cambridge) Harvesting SBML 29 March 2011 11 / 28
Harvesting SBML
Ontological commitmentRule 1: models
Model M annotated with A1:
M represents an object O1
O1 can have functions
O1’s functions can be realized by processes
model components represent parts of O1
M SubClassOf: represents some A1
M SubClassOf: represents some (has-function some A1)
M SubClassOf: represents some (has-function some
(realized-by only A1)
Robert Hoehndorf (University of Cambridge) Harvesting SBML 29 March 2011 12 / 28
Harvesting SBML
Ontological commitmentBioModel 82
annotated with heterotrimeric G-protein complex cycle (GO:0031684):
represents an object O1
O1 has a function F1
F1 is realized by processes of the type heterotrimeric G-proteincomplex cycle
M SubClassOf: represents some O1
O1 SubClassOf: (has-function some (realized-by only
GO:0031684)
Robert Hoehndorf (University of Cambridge) Harvesting SBML 29 March 2011 13 / 28
Harvesting SBML
Ontological commitmentRule 2: Compartments
Compartment C annotated with A2:
represents an object O2
part of the O1
compartment’s species represent objects that are located in O2
C SubClassOf: represents some A2
A2 SubClassOf: located-in some A1
Robert Hoehndorf (University of Cambridge) Harvesting SBML 29 March 2011 14 / 28
Harvesting SBML
Ontological commitmentCompartment “Cell” in BioModel 82
annotated with Cell (GO:0005623):
represents an object O2
O2 is a kind of Cell
O2 is part-of O1
C SubClassOf: represents some O2
O2 SubClassOf: Cell and part-of some O1
O2 SubClassOf: Cell and part-of some (has-function
some (realized-by only GO:0031684))
Robert Hoehndorf (University of Cambridge) Harvesting SBML 29 March 2011 15 / 28
Harvesting SBML
Ontological commitmentCompartment “Cell” in BioModel 82
annotated with Cell (GO:0005623):
represents an object O2
O2 is a kind of Cell
O2 is part-of O1
C SubClassOf: represents some O2
O2 SubClassOf: Cell and part-of some O1
O2 SubClassOf: Cell and part-of some (has-function
some (realized-by only GO:0031684))
Robert Hoehndorf (University of Cambridge) Harvesting SBML 29 March 2011 15 / 28
Harvesting SBML
Ontological commitmentRule 3: Species
represents an object O3
O3 can have functions
O3’s functions can be realized by processes
O3 can have qualities (concentration, amount, charge,...)
located in O2
Robert Hoehndorf (University of Cambridge) Harvesting SBML 29 March 2011 16 / 28
Harvesting SBML
Ontological commitmentSpecies GTP in “Cell” in BioModel 82
annotated with GTP (CHEBI:15996):
represents an object O3
O3 is a kind of GTP
O3 is located-in O2
S SubClassOf: represents some O3
O3 SubClassOf: GTP and located-in some O2
O3 SubClassOf: GTP and located-in some (Cell and
part-of some (has-function some (realized-by only
GO:0031684)))
Robert Hoehndorf (University of Cambridge) Harvesting SBML 29 March 2011 17 / 28
Harvesting SBML
Ontological commitmentReaction
represents an object O3 with a function F
F is realized by P
P has participants (inputs, outputs and modifiers) O4
O4 are objects represented by species
P occurs in O1
Robert Hoehndorf (University of Cambridge) Harvesting SBML 29 March 2011 18 / 28
Harvesting SBML
Ontological commitmentReaction GTP-binding in BioModel 82
annotated with GTP binding (GO:0005525):
represents an object O4
O4 has a function F4
F4 is a kind of GTP binding
F4 is realized by P4
P4 has-input O3 (GTP)
R SubClassOf: represents some (has-function some F4)
F4 SubClassOf: GTP binding and realized-by only P
P SubClassOf: has-input some O3
Robert Hoehndorf (University of Cambridge) Harvesting SBML 29 March 2011 19 / 28
Harvesting SBML
Ontological commitmentReaction GTP-binding in BioModel 82
BIOMD0000000082 - Thomsen1988 AdenylateCyclase Inhibition
represents
has-function (realized-by)heterotrimeric G-protein complex cycle
Compartment "cell"
World of BIOMD0000000082
Cell inWorld of BIOMD0000000082
part-ofWorld of BIOMD0000000082
has-part Cell
GTP
GTPhas-part GTP
part-of Cell inWorld ofBIOMD0000000082
Reaction: GTP binding with DRG
GTP binding in world ofBIOMD0000000082
has-part GTP binding in world ofBIOMD0000000082
has-input
represents
represents
represents*
Reactions
Parameter
GDPDRG
Robert Hoehndorf (University of Cambridge) Harvesting SBML 29 March 2011 20 / 28
Harvesting SBML
Ontological commitmentBioModels Result
Ontologies:
FMA
ChEBI
GO
Celltype
PATO
(KEGG, Reactome)
Result on BioModels:
more than 300,000 classes
more than 800,000 axioms
90,000 complex model annotations
http://sbmlharvester.googlecode.com
Robert Hoehndorf (University of Cambridge) Harvesting SBML 29 March 2011 21 / 28
Harvesting SBML
InconsistencyCompartments/species annotated with functions or processes
Robert Hoehndorf (University of Cambridge) Harvesting SBML 29 March 2011 22 / 28
Harvesting SBML
InconsistencyBiological inconsistency: Biomodel 176
Robert Hoehndorf (University of Cambridge) Harvesting SBML 29 March 2011 23 / 28
Harvesting SBML
InconsistencyBiological inconsistency: Biomodel 176
[Term]
id: GO:0016887
name: ATPase activity
is a: GO:0017111 ! nucleoside-triphosphatase activity
intersection of: GO:0003824 ! catalytic activity
intersection of: has input CHEBI:15377 ! water
intersection of: has input CHEBI:15422 ! ATP
intersection of: has output CHEBI:16761 ! ADP
intersection of: has output CHEBI:26020 ! phosphates
Robert Hoehndorf (University of Cambridge) Harvesting SBML 29 March 2011 24 / 28
Harvesting SBML
Knowledge retrieval
Query Query string # results
Contradictory defined entities Nothing 4,899
Models which represent a pro-cess involving sugar
model-of some (has-part some (has-function
some (realized-by only (has-participant some
sugar))))
54
Parts of BIOMD0000000015 thatrepresent processes involvingsugar
part-of some BIOMD0000000015 and represents
some (has-function some (realized-by only
(has-participant some sugar)))
29
Model entities that represent thecell cycle
represents some (has-part some (has-function
some (realized-by only ’cell cycle’)))
14
Model entities that representmutagenic central nervous sys-tem drugs in the gastrointestinalsystems
represents some (has-part some (’has role’
some ’central nervous system drug’ and
’has role’ some mutagen and part-of some
’Gastrointestinal system’)
2
Model entities that representcatalytic activity involving sugarin the endocrine pancreas
represents some (has-function some
(realized-by only (realizes some ’catalytic
activity’ and has-participant some (sugar
and contained-in some (part-of some
’Endocrine pancreas’)))))
4
Robert Hoehndorf (University of Cambridge) Harvesting SBML 29 March 2011 25 / 28
Conclusions
Future researchTowards integration of systems biology and biomedical ontology
extension to other modelling frameworks (CellML, FieldML, ...)
application to other resources
YeastNet
knowledge discovery
ontology of functions (of chemicals)model comparisonmodel composition
Robert Hoehndorf (University of Cambridge) Harvesting SBML 29 March 2011 26 / 28
Conclusions
Acknowledgements
George Gkoutos
Michel Dumontier
Dan Cook
Bernard de Bono
John Gennari
Pierre Grenon
Sarala Wimalaratne
Robert Hoehndorf (University of Cambridge) Harvesting SBML 29 March 2011 27 / 28
Conclusions
Thank you!
Biomodels, YeastNet in OWL:http://sbmlharvester.googlecode.com
Modularization:http://el-vira.googlecode.com
Robert Hoehndorf (University of Cambridge) Harvesting SBML 29 March 2011 28 / 28
