Semantic Mediation in myGrid

Chris Wroe

Manchester University

• UK e-Science Pilot Project.• Oct 2001 – April 2005.• £3.4 million.

• £0.4 million studentships.

Newcastle

NottinghamManchester

Southampton

Hinxton

Sheffield

Data-intensive bioinformatics

ID MURA_BACSU STANDARD; PRT; 429 AA.DE PROBABLE UDP-N-ACETYLGLUCOSAMINE 1-CARBOXYVINYLTRANSFERASEDE (EC 2.5.1.7) (ENOYLPYRUVATE TRANSFERASE) (UDP-N-ACETYLGLUCOSAMINEDE ENOLPYRUVYL TRANSFERASE) (EPT).GN MURA OR MURZ.OS BACILLUS SUBTILIS.OC BACTERIA; FIRMICUTES; BACILLUS/CLOSTRIDIUM GROUP; BACILLACEAE;OC BACILLUS.KW PEPTIDOGLYCAN SYNTHESIS; CELL WALL; TRANSFERASE.FT ACT_SITE 116 116 BINDS PEP (BY SIMILARITY).FT CONFLICT 374 374 S -> A (IN REF. 3).SQ SEQUENCE 429 AA; 46016 MW; 02018C5C CRC32; MEKLNIAGGD SLNGTVHISG AKNSAVALIP ATILANSEVT IEGLPEISDI ETLRDLLKEI GGNVHFENGE MVVDPTSMIS MPLPNGKVKK LRASYYLMGA MLGRFKQAVI GLPGGCHLGP RPIDQHIKGF EALGAEVTNE QGAIYLRAER LRGARIYLDV VSVGATINIM LAAVLAEGKT IIENAAKEPE IIDVATLLTS MGAKIKGAGT NVIRIDGVKE LHGCKHTIIP DRIEAGTFMI

Web Service (Grid Service) communication fabricWeb Service (Grid Service) communication fabric

AMBITText Extraction

Service

Provenance

Personalisation

Event Notification

Gateway

Service and WorkflowDiscovery

myGrid Information Repository

Ontology Mgt

Metadata Mgt

Work bench Taverna Talisman

Native Web Services

SoapLab

Web Portal

Legacy apps

Registries

Ontologies

FreeFluo Workflow Enactment Engine

OGSA-DQPDistributed Query Processor

Bio

info

rmat

icia

nsT

ool P

rovi

ders

Ser

vice

Pro

vide

rsA

pplicationsC

ore servicesE

xternal servicesService Stack

Views

Legacy apps

GowLab

Workflow approach

Grave’s Disease

Workflow approach II

Issues

• Connecting web services together– Shim services

• Connecting data to web services– Data provenance delivered by LSIDs

• Connecting data to data– Distributed Query Processing

Technology

– Resource Description Framework• Representing metadata about data and services

– Ontology Web Language• Representing concepts and classifications

myGrid & Bioinformatics world

• Automating mainstream, well known tasks

• Well known mature data formats

• Often no formal description of formats

• Lots of code to manipulate formats already exists (BioPerl, BioJava …)

• Semantic mediation work in progress..

Williams-Beuren Syndrome Workflow

Main Bioinformatics Applications

Explore gaps regions within the W-B Critical Region

Main Bioinformatics

Services

Main Bioinformatics

Application

Main Bioinformatics

Application

SHIM Services

Williams Example (simple)

Genbankretrieval service

GenscanGene predication service

Genbank recordhas_part genomic sequence

genomic sequence in

Genbank record FASTA sequence

Semantic level

Syntactic level

Sample Genbank RecordLOCUS AY214156 1065 bp mRNA linear VRT 07-MAY-2004

DEFINITION Oncorhynchus nerka RH1 opsin mRNA, complete cds.

ACCESSION AY214156

VERSION AY214156.1 GI:37787241

KEYWORDS .

SOURCE Oncorhynchus nerka (sockeye salmon)

ORGANISM Oncorhynchus nerka

Eukaryota; Metazoa; Chordata; Craniata; Vertebrata; Euteleostomi;

Actinopterygii; Neopterygii; Teleostei; Euteleostei;

Protacanthopterygii; Salmoniformes; Salmonidae; Oncorhynchus.

REFERENCE 1 (bases 1 to 1065)

AUTHORS Dann,S.G., Allison,W.T., Levin,D.B., Taylor,J.S. and Hawryshyn,C.W.

TITLE Salmonid opsin sequences undergo positive selection and indicate an

alternate evolutionary relationship in oncorhynchus

JOURNAL J. Mol. Evol. 58 (4), 400-412 (2004)

PUBMED 15114419

REFERENCE 2 (bases 1 to 1065)

AUTHORS Dann,S.G., William,A.E., David,L.B. and Craig,H.W.

TITLE Direct Submission

JOURNAL Submitted (08-JAN-2003) Biology, University of Victoria, PO Box

3020 Stn CSC, Victoria, British Columbia V8W 3N5, Canada

FEATURES Location/Qualifiers

source 1..1065

/organism="Oncorhynchus nerka"

/mol_type="mRNA"

/db_xref="taxon:8023"

CDS 1..1065

/codon_start=1

/product="RH1 opsin"

/protein_id="AAP58347.1"

/db_xref="GI:37787242"

/translation="MNGTEGPDFYVPMSNATGIVRNPYEYPQYYLVSPAAYSLMAAYM

FFLILTGFPINFLTLYVTIEHKKLRTALNYILLNLAVADLFMVIGGFTTTMYTSMHGY

FVFGRTGCNIEGFCATHGGEIALWSLVVLAIERWLVVCKPISNFRFSETHAIIGVAFT

WVMAAACSVPPLLGWSRYIPEGMQCSCGIDYYTRAPDINNESFVIHMFVVHFMIPLFI

ISFCYGNLLCAVKAAAAAQQESETTQRAEREVTRMVIMMVVSFLVCWVPYASVAWYIF

CNQGTEFGPVFMTIPAFFAKSSSLYNPLIYVLMNKQFRNCMITTLCCGKNPFEEEEGA

STTASKTEASSVSSSSVAPA"

ORIGIN

1 atgaacggca cagagggacc agatttctac gtccctatgt ccaatgctac tggcattgtt

61 aggaacccct atgaataccc ccagtactac cttgtcagcc cagcggcgta ctcactcatg

121 gctgcctaca tgttcttcct catcctcacc ggcttcccca tcaacttcct cacactctat

181 gtcaccatcg agcacaaaaa gctgaggacc gccctgaact acatcctgct gaacctggct

241 gtggccgatc tcttcatggt aatcggaggc ttcaccacta cgatgtacac ctccatgcat

301 ggctatttcg tctttggaag aacgggctgc aacatcgagg gattctgtgc tacccatggt

361 ggtgagattg ccctatggtc cctggttgtc ctggctattg agaggtggtt ggtcgtctgc

421 aaacctatta gcaacttccg cttcagtgag acccatgcca tcataggcgt ggcctttacc

481 tgggtcatgg ctgctgcttg ctccgtcccc cctctgcttg ggtggtcccg ctatatcccc

541 gaaggcatgc agtgctcatg tggaattgac tactacacgc gcgcccctga catcaacaat

601 gagtcctttg tcatccacat gttcgttgtc cactttatga ttcccctgtt catcatctcc

661 ttctgctacg gcaacctgct ctgcgctgtc aaggcagctg ccgccgccca gcaggagtct

721 gagaccaccc agagggctga gagggaagtg acccgcatgg tcatcatgat ggtcgtctcc

781 ttcctagtgt gctgggtgcc ctacgccagc gtggcctggt atatcttctg caaccaggga

841 acagagttcg gccccgtctt catgacaatt ccggcattct ttgccaagag ttcgtccctg

901 tacaaccctc tcatctacgt gttgatgaac aagcagttcc gcaactgcat gatcaccacc

961 ctgtgctgtg ggaagaaccc cttcgaggag gaggagggag cctccaccac tgcctccaag

1021 accgaggcct cctccgtgtc ctccagctcc gtggctcctg cataa

//

FASTA

>gi|37787241|gb|AY214156.1| Oncorhynchus nerka RH1 opsin mRNA, complete cds ATGAACGGCACAGAGGGACCAGATTTCTACGTCCCTATGTCCAATGCTACTGGCATTGTTAGGAACCCCT ATGAATACCCCCAGTACTACCTTGTCAGCCCAGCGGCGTACTCACTCATGGCTGCCTACATGTTCTTCCT CATCCTCACCGGCTTCCCCATCAACTTCCTCACACTCTATGTCACCATCGAGCACAAAAAGCTGAGGACC GCCCTGAACTACATCCTGCTGAACCTGGCTGTGGCCGATCTCTTCATGGTAATCGGAGGCTTCACCACTA CGATGTACACCTCCATGCATGGCTATTTCGTCTTTGGAAGAACGGGCTGCAACATCGAGGGATTCTGTGC TACCCATGGTGGTGAGATTGCCCTATGGTCCCTGGTTGTCCTGGCTATTGAGAGGTGGTTGGTCGTCTGC AAACCTATTAGCAACTTCCGCTTCAGTGAGACCCATGCCATCATAGGCGTGGCCTTTACCTGGGTCATGG CTGCTGCTTGCTCCGTCCCCCCTCTGCTTGGGTGGTCCCGCTATATCCCCGAAGGCATGCAGTGCTCATG TGGAATTGACTACTACACGCGCGCCCCTGACATCAACAATGAGTCCTTTGTCATCCACATGTTCGTTGTC CACTTTATGATTCCCCTGTTCATCATCTCCTTCTGCTACGGCAACCTGCTCTGCGCTGTCAAGGCAGCTG CCGCCGCCCAGCAGGAGTCTGAGACCACCCAGAGGGCTGAGAGGGAAGTGACCCGCATGGTCATCATGAT GGTCGTCTCCTTCCTAGTGTGCTGGGTGCCCTACGCCAGCGTGGCCTGGTATATCTTCTGCAACCAGGGA ACAGAGTTCGGCCCCGTCTTCATGACAATTCCGGCATTCTTTGCCAAGAGTTCGTCCCTGTACAACCCTC TCATCTACGTGTTGATGAACAAGCAGTTCCGCAACTGCATGATCACCACCCTGTGCTGTGGGAAGAACCC CTTCGAGGAGGAGGAGGGAGCCTCCACCACTGCCTCCAAGACCGAGGCCTCCTCCGTGTCCTCCAGCTCC GTGGCTCCTGCATAA

Williams Example (simple)

Genbankretrieval service

GenscanGene predication service

Genbank recordhas_part genomic sequence

genomic sequence in

Genbank record FASTA sequence

Semantic level

Syntactic level

EMBOSS seqret service

Genbank service

Graves disease

Array Express Gene clustering service

Microarray expression data out

Microarray expression data in

Affymetrix CEL file Treeview format

Semantic level

Syntactic level

Example data

CellHeader=X Y MEAN STDV NPIXELS

0 0 112.0 24.4 25

1 0 10699.0 1340.6 20

2 0 147.0 42.4 25

3 0 10602.0 2126.2 25

4 0 100.8 29.9 20

5 0 96.0 11.9 25

6 0 9829.0 1983.4 25

7 0 133.3 21.6 20

8 0 9092.0 1470.7 25

CEL format

Probe_Id Sample1236

1000_at 147

1001_at 96

1002_at -59

Treeview format

Template

Cell header Probe ID

2 0 1000_at

5 0 1001_at

2 3 1002_at

Graves disease

Array Express Gene clustering service

Microarray expression data out

Microarray expression data in

Affymetrix CEL file Treeview format

Semantic level

Syntactic level

AffyR service

Template file

Classification of shims

Shim service FILTER

MAPPER DEREFERENCER TRANSLATOR

syntax (e.g. GenBank to EMBL) data (e.g. DNA to protein)

TRANSFORMER SIFTER (sql SELECT type operation) PARSER (sql PROJECT type operation) -

also known as SPLITTER or DECOMPOSER COMPARER SORTER

Defn: experimentally neutral service used to connect domain services that don’t quite fit

Providing more assistance

Taverna workbench

1. RegisterTaverna workbench

3. Query

Pedro

2. Annotate

operation

name, descriptioninputoutputtaskmethodresourceapplication

workflow

bioMoby service

WSDL operation

Soaplab service

service

name, descriptionauthororganisation

WSDL service

parameter

name, descriptionsemantic typeformattransport typecollection typecollection format

myGrid’s model of services

Service Description Flow

DiscoveryClient

SemanticIndexing

Component

Registry

XML document describing service

Extract servicedescriptions toreason over

Pedro

Jena RDF repository

Instance Store

FACT DL reasoner

<serviceDescription> <organisation>http://genetics.man.ac.uk</organisation> <operation> <name>execute</name> <task>http://www.mygrid.org.uk/ontology#pairwise_local_aligning</task> …..

Pedro

XML

RDF

Queries possible within RDF repository:

Find me an operation called “exec*”Find me a service provided by groups working on Williams

diseaseFind me an operation which performs aligning?

RDF

a1234

a2

“execute”

a3

http://genetics.man.ac.uk

#service

#local_pairwise_aligning

#operation

published_bytype

type

subclass

name

task

#aligning

hasOperation

RDF

a1234

a2

“execute”

a3

http://genetics.man.ac.uk

#service

#local_pairwise_aligning

#operation

published_bytype

type

subclass

name

task

#aligning

Queries not possible:Find me an operation which performs aligning which is local?Where does this service fit into a classification

hasOperation

OWL classes#service

#local_pairwise_aligning

#operation

Owl property restriction: hasOperation

Owl property restriction: performsTask

Most specific class expression extracted

Definition: Service which has an operation which performs the task local pairwise aligning

OWL classes

service

aligning service

local aligning service

pairwise local aligning service

Each service class has its own property based

OWL definition

a1234 Instance store indexes our service instance in the appropriate place Classification calculated

by the FACT reasoner using property based

definitions

Query by navigation

Service browser

Service classified by task

Use of ontologies

• Property based classification requires property based modelling

• Advantages– Explicit, machine interpretable, easier to

maintain large ontologies with polyhierarchies

• Disadvantages– Complex definitions take time/ skill to author,

require expert domain knowledge– Difficult to present back to the user

Property based classification on steroids

RNA sequence data

DNA sequence data

nucleic acid sequence data

Data

Property based classification on steroids

RNA sequence

DNA sequence

nucleic acid sequence

RNA sequence data

DNA sequence data

nucleic acid sequence data

encodes

Data Feature

Property based classification on steroids

RNA

DNA

nucleic acid

RNA sequence

DNA sequence

nucleic acid sequence

RNA sequence data

DNA sequence data

nucleic acid sequence data

encodes sequence_of

Data Feature Biological Concept

Property based classification on steroids

ribonucleotide

deoxyribonucleotide

nucleotide

RNA

DNA

nucleic acid

RNA sequence

DNA sequence

nucleic acid sequence

RNA sequence data

DNA sequence data

nucleic acid sequence data

encodes sequence_of polymer_of

Data Feature Biological Concept

Property based classification on steroids

ribonucleotide

deoxyribonucleotide

nucleotide

RNA

DNA

nucleic acid

RNA sequence

DNA sequence

nucleic acid sequence

RNA sequence data

DNA sequence data

nucleic acid sequence data

encodes sequence_of polymer_of

Data Feature Biological Concept

Human readable ontologies

GROWL parser

OWL API

Reasoner

OWL API

GROWL renderer

Only data to hand

• Metadata associated with data items.

• Life science identifier (LSID) protocol used to retrieve metadata.

• Metadata model similar to service parameter Data item

name, descriptionsemantic typeformatcollection typecollection format

Workflow run

Workflow design

Experiment design

Project

Person

Organisation

Process

Service

Event

Data item

Data itemData item

data derivation e.g. output data derived from input data

knowledge statementse.g. similar protein sequence to

instanceOf

partOf componentProcesse.g. web service invocation of BLAST @ NCBI

componentEvente.g. completion of a web service invocation at 12.04pm

runBye.g. BLAST @ NCBI

run for

Organisation level provenance Process level provenance

Data/ knowledge level provenance

Pro

vena

nce

(1)

User can add templates to each workflow process to determine links between data items.

19747251 AC005089.3831Homo sapiens BAC

clone CTA-315H11 from 7, complete sequence15145617 AC073846.6

815Homo sapiens BAC

clone RP11-622P13 from 7, complete sequence15384807 AL365366.20

46.1Human DNA sequence

from clone RP11-553N16 on chromosome 1, complete sequence7717376 AL163282.2

44.1Homo sapiens

chromosome 21 segment HS21C08216304790 AL133523.5

44.1Human chromosome 14

DNA sequence BAC R-775G15 of library RPCI-11 from chromosome 14 of Homo sapiens (Human), complete sequence34367431 BX648272.1

44.1Homo sapiens mRNA;

cDNA DKFZp686G08119 (from clone DKFZp686G08119)5629923 AC007298.17

44.1Homo sapiens 12q22

BAC RPCI11-256L6 (Roswell Park Cancer Institute Human BAC Library) complete sequence34533695 AK126986.1

44.1Homo sapiens cDNA

FLJ45040 fis, clone BRAWH302048620377057 AC069363.10

44.1Homo sapiens

chromosome 17, clone RP11-104J23, complete sequence4191263 AL031674.1

44.1Human DNA sequence

from clone RP4-715N11 on chromosome 20q13.1-13.2 Contains two putative novel genes, ESTs, STSs and GSSs, complete sequence17977487 AC093690.5

44.1Homo sapiens BAC

clone RP11-731I19 from 2, complete sequence17048246 AC012568.7

44.1Homo sapiens

chromosome 15, clone RP11-342M21, complete sequence14485328 AL355339.7

44.1Human DNA sequence

from clone RP11-461K13 on chromosome 10, complete sequence5757554 AC007074.2

44.1Homo sapiens PAC

clone RP3-368G6 from X, complete sequence4176355 AC005509.1

44.1Homo sapiens

chromosome 4 clone B200N5 map 4q25, complete sequence2829108 AF042090.1

44.1Homo sapiens

chromosome 21q22.3 PAC 171F15, complete sequence

>gi|19747251|gb|AC005089.3| Homo sapiens BAC clone CTA-315H11 from 7, complete sequenceAAGCTTTTCTGGCACTGTTTCCTTCTTCCTGATAACCAGAGAAGGAAAAGATCTCCATTTTACAGATGAGGAAACAGGCTCAGAGAGGTCAAGGCTCTGGCTCAAGGTCACACAGCCTGGGAACGGCAAAGCTGATATTCAAACCCAAGCATCTTGGCTCCAAAGCCCTGGTTTCTGTTCCCACTACTGTCAGTGACCTTGGCAAGCCCTGTCCTCCTCCGGGCTTCACTCTGCACACCTGTAACCTGGGGTTAAATGGGCTCACCTGGACTGTTGAGCG

urn:lsid:taverna:datathing:15

..BLAST_Report

rdf:type

urn:lsid:taverna:datathing:13

..similar_sequences_to

.. nucleotide_sequence

rdf:type

service invocation

..created_by

workflow invocation

workflow definition

experiment definition

project

person

group

service description

organisation

..described_by

..run_during

..invocation_of

..part_of

..works_for

..part_of

..part_of

..author

..author

..run_for

A B

..masked_sequence_of

..filtered_version_of

Relationship BLAST report has with other items in the repository

Other classes of information related to BLAST report

Provenance tracking

Using IBM’s HaystackGenBank

record

Portion of the Web of

provenance

Managing collection of

sequences for review

Storage

• LSID has no protocol for storage

• Taverna/ Freefluo implements its own data/ metadata storage protocol

Taverna/Freefluo

Metadata Store

Data store

Publish interface

data

metadata

Retrieval• LSID protocol used to retrieve data and

metadata

• Query handled separately

Metadata Store

Data store

LSID interface

LSID aware client

Query

RDF aware client

Queries within Workflows

Grid Data Servicequery query result

Semantic content of result depends on query and data source schema

Select GO_ID FROM GO WHERE GO.term LIKE “enzyme activity”;

Select GO_Annotation_ID FROM GOAWHERE GO.term LIKE “enzyme activity”;

Gene ontology term ID

protein ID

Distributed Query Processing

• DQP linked with the OGSA-DAI activity

• Built within myGrid project

• Plans execution of a query over multiple Grid Data Services

• Each Grid Data Service provides schema metadata

• Currently no semantic mediation

Example query• select p.proteinId, blast(p.sequence)

from p in protein, t in proteinTermwhere t.termId = 'GO:0008372' andp.proteinId = t.proteinId

• “Select proteins and homologous proteins fromSWISS-PROT which have been annotated withGO:008372”

Gene ontology database SWISS-PROT protein database

t.proteinId p.proteinId

Data encoding the identity of a protein in SWISS-PROT namespace

Data encoding the identity of a protein in SWISS-PROT namespace

=

DQP Plan

Query 1: Select motifs for antigenic human proteins that participate in apoptosis and are homologous to the lymphocyteassociated receptor of death (also known as lard).

Translation: Select patterns in the proteins that invoke an immunological response and participate in programmed cell death thatare similar in their sequence of amino acids to the protein that is associated with triggering cell death in the white cells of theimmune system.

(A) Ontology expression: Motif which <isComponentOf (Protein which <hasOrganismClassification Species functionsInProcess Apoptosis hasFunction Antigen isHomologousTo Protein which <hasName ProteinName>)>)>

Species: Is instantiated by value “human”ProteinName: Is instantiated by value “lard”

TAMBIS I

TAMBIS II

• Informal query plan:• Select proteins with protein name “lard” from SWISS-PROT• Execute a BLAST sequence alignment process against

SWISS-PROT results• Check the entries for apoptosis process and antigen function• Pass the resultant sequences to PROSITE to scan for their

motifs

• CPL expression:set-unique {(#motif1:motif1)I

\protein3 <- get-sp-entries-by-de("lard"), \protein2 <- do-blastp-by-sq-in-entry(protein3),

Check-sp-entries-by-kwd("apoptosis",protein2), check-sp-entries-by-de("antigen",protein2),

Check-sp-entry-for-species("human",protein2), \motif1 <- do-ps-scan-by-sq-in-entry(protein2)}

select p.proteinId, blast(p.sequence)from p in protein, t in proteinTermwhere t.termId = 'GO:0008372' andp.proteinId = t.proteinId

• How we did it in the past– Service type directory

• How we currently plan to do it– Shims, genbank, microarray

• How we may want to do it in the future– DQP & TAMBIS

Overview

• We’re not attacking the same problem

• When would your problem become our problem

• Common descriptions of the core entities involved.– Data items, Datasets, Services.