acgt: open grid services for improving medical knowledge discovery
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ACGT: Open Grid Services for Improving Medical Knowledge Discovery. Stelios G. Sfakianakis, FORTH. The ACGT vision & principles. The ultimate objective of the ACGT project is the provision of a unified technological infrastructure which will facilitate - PowerPoint PPT PresentationTRANSCRIPT
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ACGT:Open Grid Services for Improving Medical
Knowledge Discovery
Stelios G. Sfakianakis, FORTH
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The ACGT vision & principles
The ultimate objective of the ACGT project is the provision of a unified technological infrastructure which will facilitate
integrated access to multi-level biomedical datadevelopment or re-use of open source analytical tools, accompanied with the appropriate meta-data allowing their discovery and orchestration into complex workflows.
ACGT will deliver a European Biomedical GRID infrastructure offering seamless mediation services for sharing data and data-processing methods and tools, and advanced security;ACGT
focuses on clinical trials on Cancer (Wilms tumor, Breast) andis based on the principles of
Open access (among trusted partners)Open source
is not a standards generating exercise but a standards adopting one.
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Enabling dynamic Virtual Organizations
Ontologies and mediation tools
Basic GRID technology and security
D
D
D
U
U
U
D
D
Clinical Trials …U
User Dataand Public Databases Layer
KnowledgeDiscovery Tools D
D
Simulation and Visualization Tools
UD
D
D
D
Distributed multilevelBiomedical Data
The A
CG
T Integration Layer, the
AC
GT
Tools and S
ervices
User Applications and services layer in support of
U
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The ACGT Virtual Organizations
Grid Portal
VVirtual OOrganizations
Grid Services Infrastructure(VO Manag., Metadata, Registry,
Publishing, Query, Invocation, Security, etc.)
Tool 1
Tool 2
Grid Data Service
Analytical Services
Clinical data Research
Center
Microarray
Grid Data Service
Image
Tool 2
Tool 3
Research
Center
Analytical Services
Grid Data Service
Grid-Enabled Client
ResearchCenter
Gene Database
Protein Database
Tool 3
Tool 4
Grid Data Services
Analytical Services
Grid Data Service
Public data
& tools
Tool n
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Discovery and Orchestration of Services
2D/3D visualization for in silico models
ACGT experiment topology
Microarray data processing for molecular classification of disease
Analytical Services
Data access Services
DM/KDD and visualization services
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The ACGT clinical trials
Multicentric TOP trial – Breast CancerSIOP 2002 – paediatric nephroblastomaIn Silico modeling and simulation of tumor growth & response to treatment Breast Ca
MulticentricOncogenomic Study
1
NephroblastomaMulti-centricOncogenomic Study
2
UoC
UoO
UoS
JBI
IEO
FORTH
In Silico Oncology Study
3
Prolipsis
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Main challenges in ACGT
Grid middleware services, enabling large-scale (semantic, structural, and syntactic) interoperation among biomedical resources and services;
Master ontology (on Cancer) through semantic modelling of biomedical concepts using existing ontologies and ontologies developed for the needs of the project;
Open source bioinformatic tools and other analytical services;
Semantic annotation and advertisement of biomedical resources, to allow metadata-based discovery and query of tools, and services;
Orchestration of data access and analytical services into complex eScience workflows for post genomic clinical research and trials on cancer;
Meta-data descriptions of clinical trials to provide adequate provenance information for future re-use, comparison, and integration of results;
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Major Challenge: Semantic Interoperability
The bottleneck is not so much about:
computational needs,the volume of data, orperformance issues in accessing/transferring data;
It’s integration and semantic interoperability;
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Data Integration Impediments
HeterogeneitySyntactic: Relational (SQL) Databases, web accessible databases, …Structural: Different schemas and formatsSemantic: Different vocabularies and semantics
Security related:Different access policies: some data sources require authentication, whereas others are publicSensitive and confidential data: patient names or other identifying traits should be hidden (anonymization, pseudonymization)
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Required Services
The primary services required for supporting the identified scenarios fall into four categories:
services for access and retrieval of data , that is: internal phenotypical (clinical and imaging) DBs and other “-omic” DBs, as well as external biomedical databases;services that are the analytical and visualization tools, that is: computational analysis, simulations, knowledge extraction, exposed as Grid (web) services;services for forming and executing eScience Workflows, that is:
workflow management services, information management services, and distributed database query processing;
semantic services for discovering services and workflows, and managing metadata, such as:
ontologiesmetadataprovenance
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The ACGT ConsortiumUni Lund
SIVECO
Uni Oxford
Uni Madrid, Uni Malaga
Uni Amsterdam, Philips
FORTH, Uni HospCrete, ICCS-NTU Athens, Biovista
Uni Hamburg, Uni HospSaarland, IFOMISFraunhofer (IBMT, AiS), Uni Hannover
PSNC Poznan
J. Bordet Institute, Custodix, Uni Namur
INRIA, HealthGrid, ERCIM
SIB Lausanne
Uni Hokkaido
Funding: ~18 MEuro, Time plan: 1/2/2006 – 31/1/2010
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Thank you!