One good source of such data is GEO, NCBI's Gene Expression Omnibus:
http://www.ncbi.nlm.nih.gov/geo/
I think there is a vast amount of work addressing this approach; see
PubMed for papers.
--Pete Szolovits
On Feb 14, 2008, at 2:54 PM, Santosh Srivastava wrote:
> This area has an inter
this area of biology is at least 10-12 years old.
There are tons and tons of literature on this...
You can get gene expression data from pubmed.
The latest trends include using SNP data, miRNA, etc. along with cross
species and gene regulatory network analysis.
On Thu, 14 Feb 2008, Santosh Srivas
Hi Santosh,
The main repositories for expression data are:
Gene Expression Omnibus (GEO): http://www.ncbi.nlm.nih.gov/geo/
Array Express: http://www.ebi.ac.uk/microarray-as/aer/?#ae-main[0]
These days, most new gene expression data is deposited in one of the these
two repositories.
There's als
This area has an interesting biology and could be a good research area
from machine learning perspective. I am also interested to know how to
analyze gene expression data using graphical model and other machine
learning techniques. It is good if there is any good review paper out
there. Plus I
Dear Colleagues,
I would be interested in learning of any recent research concerning the use of
Bayesian networks to analyze gene expression data.
Thanks much,
Rich
Richard E. Neapolitan
Professor and Chair of Computer Science
Northeastern Illinois University
5500 N. St. Louis
Chicago, Il 60625__
