Download Why teach a course in bioinformatics?

Why microarrays in a
bioinformatics class?
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Design of chips
Quantitation of signals
Integration of the data
Extraction of groups of genes with
linked expression profiles (gene
clustering)
2 important topics requiring
computers:
Data Integration
• It’s important to link the data from the array
experiment with other sequence databases
(Genbank, SwissProt, etc).
• If the activity of a gene has changed, you want
to be able to view pre-existing information about
the gene in order to explain the experimental
results.
• To exchange array data with other researchers,
you need some standardized format.
Gene Clustering
Group together genes with similar patterns of
expression:
Clustering can be thought of as forming a
phylogenetic tree of genes or tissues. Genes are
near each other on the "gene tree" if they show a
strong correlation across experiments, and tissues
are near each other on the "tissue tree" if they have
similar gene expression patterns.
Important ??
• This opens the possibility of
identifying patterns of coregulation
among genes, which, in turn,
reflects underlying regulatory
mechanisms and function
interrelationships.
• PNAS -- Alon et al. 96 (12): 6745
• Pattern searching and gene clustering of
promoter regions of Drosophila olfactory
receptors
• http://genomewww.stanford.edu/breast_cancer/mopo_clin
ical/images/supplfig4.pdf
The End
Arrays:
• Narrower terms include bead arrays, bead based
arrays, bioarrays, bioelectronic arrays, cDNA arrays,
cell arrays, DNA arrays, gene arrays, gene
expression arrays, genome arrays, high density
oligonucleotide arrays, hybridization
arrays, microelectronic arrays, multiplex DNA
hybridization arrays, nanoarrays, oligonucleotide
arrays, oligosaccharide arrays, protein arrays,
solution arrays, spotted arrays, tissue arrays, exon
arrays, filter arrays, macroarrays, small molecule
microarrays, suspension arrays, tiling arrays,
transcript arrays. Related terms include arrayed
library. See also chips, microarrays.
• To me, the most important thing that
has happened in recent years is the
rapid development of DNA chips.
Technologies have allowed highthroughput ‘transcriptome’ analysis.
That capability was introduced in the
’90s, but since then, it has become
much more powerful as the genome
project progressed. There are now
many transcriptome centers already set
up or being established. People are
using this technology for mapping gene
Many microarray experiments are
now being performed on human
cells.
• Genome is completely sequenced and
well annotated.
• Scientists are attempting to compare
normal vs. diseased tissue.