nodalpoint.org - Machine Learning for better Clinical Gene Expression Signatures - Comments

Commercial posts

dbodde — Mon, 05 Jun 2006 10:50:32 -0400

Yes, I am. That policy sounds fair enough..

Doug Bodde

So I assume you're Douglas

Greg — Mon, 05 Jun 2006 09:07:33 -0400

So I assume you're Douglas Bodde, VP Sales and Marketing from Biomind ?

I'm am not fundamentally against biotech companies posting informative news/announcements on nodalpoint. However cutting and pasting from press releases and white papers is the wrong way of going about it. It comes across as a little bit contemptuous of the people who run/frequent the site.

Please contact me if you have any questions reading site policy wrt companies/advertising etc. or reply to the post. If I don't hear anything shortly I'll unpublish this post.

Ironically this has already been indexed by google, I came across it today doing a search for 'supervised leaning and biomarkers'. I didn't see biomind.com there...

Machine Learning for better Clinical Gene Expression Signatures

dbodde — Tue, 30 May 2006 00:33:27 -0400

Machine Learning Algorithms
for Clinical and Research Microarray Data Analysis

Mining Microarray Data to Discover:

Disease Biomarkers & Complex Genetic Relationships

Biomind LLC WHITE PAPER

January 2006

Molecular biomarkers associated with disease and disease predisposition may be used for diagnostic purposes in the early detection and characterization of various disorders. Microarray and SNP data have been used extensively based upon their respectively high resolution of gene expression and polymorphism. And, while diagnostic, pharmacogenomic, and research uses for such biomarkers have proliferated, methods for their identification have standardized. Biomind has developed software which sifts through large, complex microarray datasets to accurately identify biomarkers implicit in clinical disease data. The software uses machine learning algorithms which integrate the Gene Ontology (GO) and Protein Information Resource (PIR).