respective contributions of miame, geneontology and umls for transcriptome analysis
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Respective contributions of MIAME, GeneOntology and UMLS for
transcriptome analysis
Fouzia Moussouni, Anita Burgun, Franck Le Duff,
Emilie Guérin, Olivier Loréal
INSERM U522 and Medical Informatics Laboratory,
CHU Pontchaillou
Rennes, FRANCE
Transcriptome & DNA microarraystudy of transcriptionnal response of the cell
NormalNormal PathologicPathologic
Response to a growth factor
Response to a growth factor
Response to genetic
disturbances
Response to genetic
disturbances
Response to chemics or foods
treatment
Response to chemics or foods
treatment
Pathological situations studied at INSERM U522Pathological situations studied at INSERM U522
IRON IRON overloadoverload
DNA mutation(s)DNA mutation(s)Hemochromatosis…Hemochromatosis…
Chronic liver diseasesChronic liver diseases
FibrosisFibrosis
CirrhosisCirrhosis
HepatocarcinomaHepatocarcinoma
MechanismsMechanisms
One may deposit thousands of genes
1 gene but multiple
facets !
Intensive data generation1 measure1 Expression Level
1 Spot intensity
Available knowledge on the expressed genes, that need to be
capturized and organized.
Experimental Raw Data
Nucleic Sequence components - promoters, introns, exons, transcripts, regulators, …
Chromosomal localization,
Functional proteins and known genes products,
Tissue distribution,
Known gene interactions,
Expression level in physiologic and pathologic conditions,
Known gene variations,
Clinical Implications,
Literature and bibliographic data on a gene.
One gene but multiple descriptions
ExternalSources
AnalysisGene Expressionwarehouse
Micro-arrays Substractive banks
SAGE
ClinicalData
? ? ?
Need of an integrated gene expression environment (for the liver!)
Integration
Data cleaning !
experimental data
BIO KNOWLEDGE
Gene Expression Warehouse
Standardization and controlled specification
ONTOLOGY DESIGN
Knowledge extraction and data exchange
Standardization ONTOLOGY DESIGN
Respective contributions
MIAME
UMLS
GO
MIAME
MIAME will provide a standard framework to represent the minimum information that must be reported about microarray experiments :
• Experience• Array• Samples• Hybridization • Measures• Normalisation and control
Work in progress ...
Minimum information about a microarray experiment (MIAME) toward standards for microarray data', A. Brazma, at al., Nature Genetics, vol 29 (December 2001), pp 365 - 371.
GO is an ontology for molecular biology and Genomics,
GeneOntology (GO)
But GO is not populated with :
GOAGOA
gene sequences gene products, ...
The Unified Medical Language System (UMLS) is intended to help health
professionals and researchers to use biomedical information from different sources.
UMLS
Examples from iron metabolism are studied
How pathologic disease states related to iron metabolism alteration are described in GO and UMLS ?
BIOLOGICAL MODEL FOR IRON METABOLISM
Iron metabolism diseases
IRON METABOLISM
GENES
Iron overloadaceruloplasminemia
Iron deficiency
Other diseaseshyperferritinemiacataract
PATHOLOGICSTATES
alteration
Other diseaseshyperferritinemiacataract
Iron overload due to a gene alteration
Iron overload during Aceruloplasminemia
mutation
Feroxydase activity in plasmaFe2+ Fe3+
Iron binding with plasmatic transferrin
Ceruloplasmin
Gene
THE IRON STAYS INSIDE THE CELL !!
NO
NO
BIOLOGICAL MODEL FOR IRON METABOLISM
Other diseaseshyperferritinemiacataract
IRON METABOLISM
GENES
PATHOLOGICSTATES
alteration
Iron metabolism diseases
Iron overloadaceruloplasminemia
Iron deficiency
A second scenario related to iron metabolism genes alteration
Cataract and hyperferritinemia
mutation
IRP
IRE Translation in excess
L_Ferritin
gene
L_FerritinmRNA
L_Ferritin protein in excess
CATARACT and HYPERFERRITINEMIA !
UMLS view
Cataract and hyperferritinemia
AA, Peptide or ProreinBiologically Active Substance
AA, Peptide or Protein
Ferritin
Iron compound
L_FerritinH_Ferritin
Metalloprotein
RNAbindingProtein
IronSulfurProt
Cataract
Co-occursIn Medline(freq 26)
Co-occursIn Medline
IRP
IRE
GO/ GOAnnotations view
Cataract and hyperferritinemia
FerritinHeavyChain
Cell component
Ferritin
IRP
Ferritin Light Chain
IRE
Ligand binding Prot or carrier
Ferric iron binding
Iron homeostasis
Iron transport
Hydro-lyase
Metabolism
Cataract
Link in GO Annotations DB
Target representation
Cataract and hyperferritinemia
CataractIRP
Ligand binding Prot or carrier
Ferric iron binding
Iron homeostasis
Iron transportFerritin Light Chain
FerritinHeavyChain
Ferritin
IRE HyperferritinemiaGenes
Mutated genes Dynamic linksModeling of biological functions
DNA Chips
And more generally …
Recapitulative Information on disease states, clinical treatments and
followups.Normal vs. pathologic
Information on Roles of the genes in Biological and
metabolic states
?
We need precise and dynamic models to get
the whole picture
MIAME
Information on biological
samples, experiments and results
GOA
UMLS
Gene products for Iron metabolism, as they are actually described in GO and UMLS.
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