From genes to pathways or why we do data mining to couple microarray reporter info to known protein

1
From genes to pathways or why we do data mining
to couple microarray reporter info to known
protein functions

• Rachel van Haaften
• BiGCaT Bioinformatics BMT-TU/e UM
• Maastricht May 19 2004

2
Two types of omics
Transcriptomics Microarrays Values for 20 K
genes Annotation difficult
Proteomics Currently only 2DMS Only
20-50identified proteins Annotationis
identification Plus modifications
3
Transcriptomicsgene expression arrays

• Microarrays
• relative fluorescense signals.
• Identification.

4
Proteomics2D-gel MS
Alternative splicing?
Phosphorylation?
Alternative splicing? Modification?
Phosphorylation? Modification?
Protein variants derived from single genes
5
Functional mapping-GenMAPP-

• Gene Ontology (GO) MAPPS
• contain related genes from the public Gene
  Ontology Project
• Local MAPPs
• contain pathways made by various research
  institutes

6
Gene Ontology (GO) levels (I)

The Gene Ontology (GO) project gives a consistent
descriptions of gene products from different
databases.
Amigo browser http//www.godatabase.org/cgi-bin/go
.cgi GO consortium http//www.geneontology.org
7
Gene Ontology (GO) levels (II)
8
Example GO MAPP
9
Example Local MAPP
10
Local MAPP with backpage
11
Visualize expression results
12
Visualize expression results
SwissProt
13
Annotation of genes/proteins
DatabasesBioASPlocal copies

• Array reporter
• Unigene IDs SwissProt
  IDs

14
Result
15
Understanding changes

• Steal and smartly adapt a transcriptomics tool
• GenMapp/Mappfinder
• I will show some examples