This document provides an introduction to bio-ontologies and the semantic web. It discusses what ontologies are and how they are used in the bio domain through standards like the OBO Foundry. It introduces key semantic web technologies like RDF, IRI, TTL, SPARQL and OWL that are used to represent ontologies and linked data. It provides examples of representing ontologies and data in the Turtle syntax and using semantic web standards like RDFS for defining classes, properties and basic inference.

1. Introduction to Bio
Ontologies
and The
Semantic Web
M.
Devisscher
Biological Databases

2. Overview
• Bio
ontologies
• Semantic technologies
• Practical
sessions:
– Protégé and a
bio
database
– DYI
SPARQL
endpoint

3. Introduction
• Ontologies:
what are
ontologies ?
• Ontologies in
the
bio
domain:
OBO
Foundry
• Ontologies in
the
semantic web
• OBO
• RDF,
IRI,
TTL,
SPARQL,
OWL

4. What is
an ontology ?
• Ontology =
a
specification of
a
conceptualization (Gruber 1993)
• In
practice:
controlled vocabularies
– Disambiguation (e.g.
Bank,
Running)
– Language/species
independence
• Very useful in
biology – complex
hierarchies of
terms

5. Ontologies in
the
bio
Domain
• OBO
Foundry -­‐ open
Biological and
Biomedical Ontologies
• Common
principles
• List
of
ontologies at
http://www.obofoundry.org
• OBO
is
also a
data
format
.obo

6. SideTrack – The
Gene
Ontology
• The
mother of
bio-­‐ontologies:
the
GO
– Oldest bio
– ontology
– Many practical
applications:
• Cross
species
studies
• Term
abundance studies
• GO
is
an OBO
ontology

7. SideTrack – The
Gene
Ontology
• Collection
of
terms

8. SideTrack – The
Gene
Ontology
• Relationships between terms:
– Subsumption:
is_a
– Partonomic:
part_of
• These
terms are
transitive
• Terms form
a
DAG
(directed,
acyclic graph)
• Some information
can be inferred

9. SideTrack – The
Gene
Ontology

10. SideTrack – The
Gene
Ontology

11. SideTrack – The
Gene
Ontology
• Know more:
www.geneontology.org
• AMIGO
:
the
GO
browser

12. Gene
Ontology
Annotation
• Gene
ontology
annotations
GOA
=
entities
labeled
with
GO
terms
– E.g.
Uniprot-­‐GOA

13. Semantic Technologies
• The
semantic web:
Tim
Berners Lee
et
al,
Scientific American
2001

14. Semantic Technologies
• W3C:
a
set
of
specifications
http://www.w3.org/standards/semanticweb/
• A
mature toolset
– Dedicated data
formats
– Storage
– Query
language

15. Semantic Technologies
• Basic
data
element
=
a
Triple
– A
mini
sentence
– Contains three Terms:
• Subject
Predicate Object

16. Semantic Technologies
• Representation of
triples
– Basic
data
format:
RDF/XML
– All data
expressed in
RDF
(Resource
Description
Framework)
– Several compatible
syntaxes:
TTL
(Terse Triple
Language)
most
human
readable

17. Example

18. The
Turtle Syntax
• Basic
Triple
<http://bioinformatics.be/entities#martijn>
<http://bioinformatics.be/relations#has_favorite_beer>
<http://bioinformatics.be/entities#karmeliet>.

19. The
Turtle Syntax
• Prefix
@prefix b4x: <http:bioinformatics.be/terms#>
b4x:martijn b4x:has_favorite_beer b4x:karmeliet.

20. The
Turtle Syntax
• Predicate lists
@prefix b4x: <http:bioinformatics.be/terms#> .
@prefix foaf: <http://xmlns.com/foaf/0.1/> .
b4x:martijn b4x:has_favorite_beer b4x:karmeliet;
foaf:name “Martijn Devisscher”.

21. The
Turtle Syntax
• Object
lists
@prefix b4x: <http:bioinformatics.be/terms#> .
@prefix foaf: <http://xmlns.com/foaf/0.1/> .
b4x:martijn b4x:has_favorite_beer b4x:karmeliet,
b4x:chimay_blauw;
foaf:name “Martijn Devisscher”.

22. IRI’s and Literals
• Terms can be either IRI’s,
Literals or
blank
nodes
• IRI
= Internationalized Resource
Identifier
• Unique
id – a
virtual
URI
– Example:
http://bioinformatics.be/terms#martijn
– There is
no
requirement for resolving
– Now:
Open
Data
initiatives:
please do
use resolvable
URI’s http://linkeddata.org
– Unique
identifierscan be registered on
http://identifiers.org

23. Introduction
• Literals:
can be typed,
allowed types
from the
XSD
namespace:
– E.g.
“This is
a
string
example”^^xsd:string
– E.g.
“5”^^xsd:integer
• IRI’s are
used for entities and attributes
• Literals are
used for attribute values that
aren’t entities

24. The
Turtle Syntax
• Typed literals
@prefix b4x: <http:bioinformatics.be/terms#> .
@prefix foaf: <http://xmlns.com/foaf/0.1/> .
@prefix xsd: <http://www.w3.org/2001/XMLSchema#> .
b4x:martijn b4x:has_favorite_beer b4x:karmeliet,
b4x:chimay_blauw;
b4x:length “184”^^xsd:integer;
foaf:name “Martijn Devisscher”^^xsd:string.

25. The
Turtle Syntax
• Blank
nodes
@prefix b4x: <http:bioinformatics.be/terms#> .
@prefix foaf: <http://xmlns.com/foaf/0.1/> .
@prefix xsd: <http://www.w3.org/2001/XMLSchema#> .
b4x:martijn b4x:has_favorite_beer b4x:karmeliet,
b4x:chimay_blauw;
b4x:length “184”^^xsd:integer;
foaf:name “Martijn Devisscher”^^xsd:string;
b4x:owns_cat [ b4x:color “Gray” ].

26. Classes
and Individuals
• rdf:type
@prefix b4x: <http:bioinformatics.be/terms#> .
@prefix foaf: <http://xmlns.com/foaf/0.1/> .
b4x:martijn rdf:type foaf:Person.

27. Classes
and Individuals
• Shorthand:
a
@prefix b4x: <http:bioinformatics.be/terms#> .
@prefix foaf: <http://xmlns.com/foaf/0.1/> .
b4x:martijn a foaf:Person;
foaf:knows b4x:geert.
b4x:geert a foaf:Person.

28. Example
<http://xmpl/entities#martijn>
<http://xmpl/relations#has_favorite_beer>
<http://xmpl/entities#karmeliet>.

29. Semantic Technologies
• Sets
of
triples form
a
Graph

30. Graphs
• Triples are
building
blocks of
Graphs
• Combining sets
of
triples allows the
construction of
arbitrarily complex
graphs
b4x:martijn b4x:karmeliethas_favorite_beer

31. Add meaning !
• Reuse terms from existing,
well
defined
vocabularies – ontologies (foaf,
dc,
go,
so)
• Describe new
terms =
Ontologies
• Contain
– A
crisp
human
definition
– Some machine
readable facts

32. Metadata
• Ontologies are
also described in
RDF
– RDFS:
RDF
-­‐ Schema
– OWL:
Web
Ontology Language
– Also expressed in
RDF
• For
clarity,
file
extension
can be .rdfs or
.owl

33. RDFS
Essentials
• Descriptions
– rdfs:label
– rdfs:comment

34. RDFS
• Relationships between properties,
classes
– rdfs:Class
– rdfs:subClassOf
– rdf:Property
– rdfs:subPropertyOf
– rdfs:range
– rdfs:domain

35. RDFS:
Example
@prefix rdfs: <http://www.w3.org/2000/01/rdf-­‐schema#>.
@prefix foaf: <http://xmlns.com/foaf/0.1/> .
@prefix xsd: <http://www.w3.org/2001/XMLSchema#> .
b4x:karmeliet a b4x:Trappist .
b4x:Beer a rdfs:Class .
b4x:Trappist a rdfs:Class .
b4x:Trappist rdfs:subClassOf b4x:Beer .
b4x:has_favorite_beer a rdf:Property ;
rdfs:domain foaf:Person ;
rdfs:range b4x:Beer .
b4x:Beer rdfs:subClassOf b4x:Drink .

36. Analogy
• RDF
=
database
=
data
• RDFS/OWL
=
schema
=
metadata
• Both
are
described in
RDF,
but
have
a
different
scope

37. Semantic Technologies
• Inference
– Enhance dataset
using knowledge from metadata
(e.g.
rdfs,
owl)
• Types
of
inference engines
– RDFS
inference
• RDFS
entailmentregime
– OWL
inference
• Under
active research
• Engines
exist for specific subsets of
OWL
(OWL-­‐DL)

38. RDFS
Entailment

39. RDFS:
Inference
b4x:kevin
b4x:has_favorite_beer
b4x:stella
Q:
What can we
infer from this using RDFS
entailment ?

40. RDFS:
Inference
b4x:kevin
b4x:has_favorite_beer
b4x:stella
Inferred triples:
b4x:kevin
a
foaf:Person [from domain]
b4x:stella
a
b4x:Beer
[from range]
b4x:stella
a
b4x:Drink
[from subClassOf]

41. DuckTyping
• Watch
out
with inference !
Example:
You want
to express that people can
have
lengths
b4x:length a rdf:Property;
rdfs:domain foaf:Person;
rdfs:range xsd:integer.

42. DuckTyping
• Problem:
ex:VW_Transporter b4x:length “600”^xsd:integer.
• Would infer that VW_Transporter is
a
Person
!
• This is
called DuckTyping
If
it
looks
like
a
duck,
swims
like
a
duck,
and
quacks
like
a
duck,
then
it
probably
is
a
duck

43. Task
• Find
a
solution:
express
in
rdfs that
people
can
have
lengths

44. Task
• Find
a
solution:
express
in
rdfs that
people
can
have
lengths
b4x:havingLenght a rdfs:Class.
b4x:length a rdf:Property;
rdfs:domain b4x:havingLength;
rdfs:range xsd:integer.
foaf:Person rdfs:subClassOf b4x:havingLength.

45. Storing
RDF
• As
an RDF
file
for download
• In
a
Triplestore
– Database
optimised for storing
triples
– Examples:
BlazeGraph,
Fuseki,
Sesame

46. Semantic Technologies
• Querying over
RDF
data:
SPARQL
• Cool
features:
– Distributed
querying =
actual distribution of
data
and computing
resources
– SPARQL/Update:
modify data
• SPARQL
endpoints:
SPARQL
over
HTTP

47. SPARQL
Query
Syntax
• First
example:
SELECT ?subject ?predicate ?object WHERE {
?subject ?predicate ?object.
}
(Generally
not a
good idea as
it will pull
down
the
whole dataset)
Binding
variables
Graph matching

48. ?
SELECT ?person WHERE {
?person b4x:has_favorite_beer b4x:karmeliet
}

49. ?

50. SPARQL
Query
Syntax
• Limit
result size :
SELECT ?subject ?predicate ?object WHERE {
?subject ?predicate ?object.
} LIMIT 10

51. SPARQL
Query
Syntax
• Find all classes:
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-­‐schema#>
SELECT ?class ?label WHERE {
?class a rdfs:Class.
?class rdfs:label ?label.
}
(This will only retrieve classes
that have
a
label)

52. SPARQL
Query
Syntax
• Find all classes:
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-­‐schema#>
SELECT ?class ?label WHERE {
?class a rdfs:Class.
OPTIONAL {
?class rdfs:label ?label.
}
}

53. SPARQL
Query
Syntax
• Find all classes
that contain “duck”
in
the
label:
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-­‐schema#>
SELECT ?class ?label WHERE {
?class a rdfs:Class.
?class rdfs:label ?label.
FILTER( CONTAINS (str(?label) , “duck” ) )
}

54. SPARQL
Query
Syntax
• Make
it case
insensitive:
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-­‐schema#>
SELECT ?class ?label WHERE {
?class a rdfs:Class.
?class rdfs:label ?label.
FILTER( CONTAINS ( UCASE(str(?label)) , “DUCK” ) )
}

55. SPARQL
Query
Syntax
• Search
in
specific graph:
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-­‐schema#>
SELECT ?class ?label
FROM <http://example.org/animals>
WHERE {
?class a rdfs:Class.
?class rdfs:label ?label.
FILTER( CONTAINS ( UCASE(str(?label)) , “DUCK” ) )
}

56. SPARQL
Query
Syntax
• Search
in
specific graph:
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-­‐schema#>
SELECT ?class ?label WHERE {
GRAPH <http://example.org/animals> {
?class a rdfs:Class.
?class rdfs:label ?label.
FILTER( CONTAINS ( UCASE(str(?label)) , “DUCK” ) )
}
}

57. SPARQL
Query
Syntax
• Can also search
for graphs :
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-­‐schema#>
SELECT ?g WHERE {
GRAPH ?g {
?class a rdfs:Class.
?class rdfs:label ?label.
FILTER( CONTAINS ( UCASE(str(?label)) , “DUCK” ) )
}
}

58. Summary:
Querying RDF
data
RDF
Data
Inference
Engine
RDFS/OWL
RDF
Data
Inferred
SPARQL
Endpoint

59. • Basic data element = a Triple
– A mini sentence
– Contains three Terms:
– Subject Predicate Object
• Example:
<http://xmpl/entities#martijn>
<http://xmpl/relations#has_favorite_beer>
<http://xmpl/entities#karmeliet>.
Take
home
Summary

60. • Combine triples to represent
knowledge

61. • Use terms from ONTOLOGIES
– COMMON VOCABULARIES
– POSSIBLE TO INFER
MEANING
• OMIABIS
• OBIB
• SNOMED/ICD
• MESH

62. ?
• SPARQL searches for patterns

63. ?

64. Interoperability between OBO
and
Semantic Technologies
• Originated from two separate
academic worlds
• Computing
applications of
OBO
mainly
consistencycheckingand overrepresentation
analysis
• Semantic Technologies:
much broader toolset
• Interoperability ?
– Direct
offering in
both formats
– Automated mapping

65. Where to find ontologies
• OBO
Foundry
• Bioportal;
NCBO
• Biogateway
• Bio2RDF

66. Where to find RDF
data
• Google
for SPARQL
endpoint
• =>
e.g.
EBI
databases
• Non
biological:
DBpedia

67. How
about Tim
Berners Lee’s vision
• We’re not there yet,
but
for bio
data
we’re
getting quite close
– The
explicitome
– Crowd sourcing
– Nanopublications

68. SPARQL
in
PRACTICE

69. SPARQL
:
Recap
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
SELECT ?label
FROM <http://graphName> WHERE {
?x rdfs:label ?label.
FILTER ( CONTAINS(?label, “dimethylalinine”) )
} LIMIT 10 ORDER BY ?label

70. SPARQL
:
Recap
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
SELECT ?label
FROM <http://graphName> WHERE {
?x rdfs:label ?label.
FILTER ( CONTAINS(?label, “dimethylalinine”) )
} LIMIT 10 ORDER BY ?label
• FIND
the
pattern
?x rdfs:label ?label.

71. SPARQL
:
Recap
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
SELECT ?label
FROM <http://graphName> WHERE {
?x rdfs:label ?label.
FILTER ( CONTAINS(?label, “dimethylalinine”) )
} LIMIT 10 ORDER BY ?label
• FIND
the
pattern
?x rdfs:label ?label.
• BIND
variables
?label,
?x

72. SPARQL
:
Recap
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
SELECT ?label
FROM <http://graphName> WHERE {
?x rdfs:label ?label.
FILTER ( CONTAINS(?label, “dimethylalinine”) )
} LIMIT 10 ORDER BY ?label
• FIND
the
pattern
?x rdfs:label ?label.
• BIND
variables
?label,
?x
• RETRIEVE variable
?label

73. SPARQL
:
Recap
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
SELECT ?label
FROM <http://graphName> WHERE {
?x rdfs:label ?label.
FILTER ( CONTAINS(?label, “dimethylalinine”) )
} LIMIT 10 ORDER BY ?label
• FIND
the
pattern
?x rdfs:label ?label.
• BIND
variables
?label,
?x
• RETRIEVE
variable
?label
• PREFIX:
replace
rdfs:label by
<http://www.w3.org/2000/01/rdf-schema#>

74. SPARQL
:
Recap
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
SELECT ?label
FROM <http://graphName> WHERE {
?x rdfs:label ?label.
FILTER ( CONTAINS(?label, “dimethylalinine”) )
} LIMIT 10 ORDER BY ?label
• FIND
the
pattern
?x rdfs:label ?label.
• BIND
variables
?label,
?x
• RETRIEVE
variable
?label
• PREFIX:
replace
rdfs:label by
<http://www.w3.org/2000/01/rdf-schema#>
• FILTER results
to
labels
containing
“dimethylalinine”

75. SPARQL
:
Recap
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
SELECT ?label
FROM <http://graphName> WHERE {
?x rdfs:label ?label.
FILTER ( CONTAINS(?label, “dimethylalinine”) )
} LIMIT 10 ORDER BY ?label
• FIND
the
pattern
?x rdfs:label ?label.
• BIND
variables
?label,
?x
• RETRIEVE
variable
?label
• PREFIX:
replace
rdfs:label by
<http://www.w3.org/2000/01/rdf-schema#>
• FILTER
results
to
labels
containing
“dimethylalinine”
• LIMIT
results
to
first
10
matches
ordered
by
label

76. SPARQL
:
Recap
DESCRIBE
<http://rdf.wikipathways.org/Pathway/WP1425_r74390/WP/Interaction/e077e>
• Useful
short
query
to
get
direct
links
from/to
a
given
node

77. SPARQL
REFERENCE
http://www.w3.org/TR/sparql11-­‐overview/

78. Running
SPARQL
• From
a
web
interface

79. • From
a
web
interface
• Using
http
– HTTP
GET
– HTTP
POST
:
for
larger
query
strings
– Headers
determine
response
type
(JSON,
XML,
HTML)
http://…/sparql?default-graph-uri=<http://graphName>&query=URLENCODEDQUERYSTRING
Running
SPARQL

80. BIO-­‐ONTOLOGIES

81. BioPortal

82. Access
• From
the
web
interface
!
• SPARQL
endpoint:
using
API
key;
on
request
• Running
a
local
copy:
download
VM
image;
on
request

83. Exercises
• Find
a
term
• Find
ontologies
containing
a
term
• Browse
some
ontologies
• Check
the
NCBO
annotator
!

84. BIO-­‐DATA

85. EBI
RDF
Resources

86. EBI
RDF
Resources

87. Ensembl

88. Exercise
• From
uniprot find
proteins
that
are
annotated
with
a
given
Gene
Ontology
term

89. PREFIX up:<http://purl.uniprot.org/core/>
PREFIX taxon:<http://purl.uniprot.org/taxonomy/>
PREFIX rdfs:<http://www.w3.org/2000/01/rdf-schema#>
PREFIX obo:<http://purl.obolibrary.org/obo/>
SELECT * WHERE {
?protein up:classifiedWith obo:GO_0004499.
?protein up:organism taxon:9606.
}
http://sparql.uniprot.org

90. Exercise
• From
Expression
Atlas
find
proteins
that
are
differentially
expressed
(P
<
1e-­‐12)
in
Crohn’s
disease

91. PREFIX rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX owl: <http://www.w3.org/2002/07/owl#>
PREFIX dcterms: <http://purl.org/dc/terms/>
PREFIX obo: <http://purl.obolibrary.org/obo/>
PREFIX sio: <http://semanticscience.org/resource/>
PREFIX efo: <http://www.ebi.ac.uk/efo/>
PREFIX atlas: <http://rdf.ebi.ac.uk/resource/atlas/>
PREFIX atlasterms: <http://rdf.ebi.ac.uk/terms/atlas/>
PREFIX up:<http://purl.uniprot.org/core/>
PREFIX biopax3:<http://www.biopax.org/release/biopax-level3.owl#>
SELECT distinct ?protein ?expressionValue ?pvalue WHERE {
?factor rdf:type efo:EFO_0000384 .
?value atlasterms:hasFactorValue ?factor .
?value atlasterms:isMeasurementOf ?probe .
?value atlasterms:pValue ?pvalue .
?value rdfs:label ?expressionValue .
?probe atlasterms:dbXref ?protein .
FILTER ( ?pvalue < 1e-12 )
FILTER ( strstarts(str(?protein),"http://purl.uniprot.org/uniprot/") )}
}ORDER BY ASC (?pvalue)
https://www.ebi.ac.uk/rdf/services/atlas/sparql

92. • Links
pathways
with
genes,
terms
from
Pathway,
Cell
line
and
Disease
ontology,
PubMed
references
• Models
individual
Interactions
• Can
be
downloaded
as
RDF
• Has
an
experimental
SPARQL
endpoint
WikiPathways

93. • Define
a
query
to
find
pathways
linked
to
TNFalpha gene
Exercise

94. PREFIX wp: <http://vocabularies.wikipathways.org/wp#>
PREFIX dc: <http://purl.org/dc/elements/1.1/>
PREFIX dcterms: <http://purl.org/dc/terms/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
SELECT DISTINCT ?PathwayName where {
?geneProduct a wp:GeneProduct .
?geneProduct dc:identifier ?GeneID .
?geneProduct dcterms:isPartOf ?pathway .
?geneProduct rdfs:label ?geneName .
?pathway dc:identifier ?pathwayid .
?pathway dc:title ?PathwayName .
FILTER(str(?geneName) = "TNFalpha" )
}
http://sparql.wikipathways.org

97. • Try
this,
or
another
query
– Using
web
interface
– Using
http
get
• Define
a
simple
describe
• Use
a
web
tool
to
URLEncode the
query
• Submit
query
as
a
URL
parameter
Exercise

98. DisGeNet

99. PREFIX xsd: <http://www.w3.org/2001/XMLSchema#>
PREFIX dcterms: <http://purl.org/dc/terms/>
PREFIX foaf: <http://xmlns.com/foaf/0.1/>
PREFIX skos: <http://www.w3.org/2004/02/skos/core#>
PREFIX void: <http://rdfs.org/ns/void#>
PREFIX sio: <http://semanticscience.org/resource/>
PREFIX ncit: <http://ncicb.nci.nih.gov/xml/owl/EVS/Thesaurus.owl#>
PREFIX up: <http://purl.uniprot.org/core/>
SELECT DISTINCT ?gene WHERE {
?gda sio:SIO_000628 ?gene,?disease .
?gene a ncit:C16612 .
?gene skos:exactMatch ?GeneID .
?disease a ncit:C7057 .
?disease dcterms:title ?DiseaseName .
?gda sio:SIO_000216 ?scoreIRI .
?scoreIRI sio:SIO_000300 ?score .
FILTER (?score > "0.35"^^xsd:decimal)
FILTER (contains(str(?DiseaseName),"Crohn"))
}
http://rdf.disgenet.org/lodestar

101. PREFIX rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX owl: <http://www.w3.org/2002/07/owl#>
PREFIX xsd: <http://www.w3.org/2001/XMLSchema#>
PREFIX dcterms: <http://purl.org/dc/terms/>
PREFIX foaf: <http://xmlns.com/foaf/0.1/>
PREFIX skos: <http://www.w3.org/2004/02/skos/core#>
PREFIX void: <http://rdfs.org/ns/void#>
PREFIX sio: <http://semanticscience.org/resource/>
PREFIX ncit: <http://ncicb.nci.nih.gov/xml/owl/EVS/Thesaurus.owl#>
PREFIX up: <http://purl.uniprot.org/core/>
PREFIX wp: <http://vocabularies.wikipathways.org/wp#>
PREFIX dc: <http://purl.org/dc/elements/1.1/>
PREFIX dcterms: <http://purl.org/dc/terms/>
http://rdf.disgenet.org/lodestar

102. SELECT DISTINCT ?PathwayName WHERE {
?gda sio:SIO_000628 ?gene, ?disease .
?gene a ncit:C16612 .
?disease a ncit:C7057 .
?disease dcterms:title ?DiseaseName .
?gda sio:SIO_000216 ?scoreIRI .
?scoreIRI sio:SIO_000300 ?score .
FILTER (?score > "0.35"^^xsd:decimal)
FILTER (contains(str(?DiseaseName),"Crohn"))
SERVICE <http://sparql.wikipathways.org/> {
?geneProduct a wp:GeneProduct .
?geneProduct dc:identifier ?gene .
?geneProduct dcterms:isPartOf ?pathway .
?pathway dc:identifier ?pathwayid .
?pathway dc:title ?PathwayName .
}
}
http://rdf.disgenet.org/lodestar/sparql