Week of 10/19/09

Content:

This week's lectures were on bioinformatics. Some sources of bioinformatics data were covered including genomes, proteomes, and metabolomes. Those data sources can be used to detect biomarkers that are indications of diseases. Some types of genetic analyses that are done in bioinformatics include analyses of SNPs, DNA methylation, and copy number variations. Microarrays are one type of technology that are used for those analyses. Mass spectrometry can be used for protein analyses. The FDA has approved the use of some biomarkers for testing for the presence of illnesses. Data mining can be used to identify disease associations with genetics. Chi square tests can be used to test if the occurrence of genotypes or specific alleles are more frequent in people with diseases than people without diseases. Genetic sequence alignment algorithms can be used to find differences and similarities in genetic sequences.

Dr. Dinu covered a lot of topics that are important in the field of bioinformatics. I liked how he talked about a variety of different biomarkers that can be associated with diseases. Its interesting to me to look at the list of FDA approved biomarkers for cancers. That was from 2005 also. A list of genomic biomarkers for drugs that seems current is here:

http://www.fda.gov/Drugs/ScienceResearch/ResearchAreas/Pharmacogenetics/ucm083378.htm

According to the FDA site “Pharmacogenomic information is contained in about ten percent of labels for drugs approved by the FDA.“ That is quite a lot of relevance that pharmacogenomics is having on medication. Warfarin is on that list, as mentioned in previous classes. It will be interesting to see what new pharmacogenomics discoveries happen and are relevant to medications in upcoming years.

Posted by:

Nate