In silico studies of energy metabolism of normal and diseased heart

Biotechnology research is developing into genomic analyses that involve the simultaneous monitoring of thousands of genes. The development of various bioinformatics resources that provide efficient access to information is ne cessary. We have used single-pass sequencing of randomly selected cDNA clon es to generate expressed sequence tags (ESTs). These ESTs data has been wid ely used to study gene expression in a variety of heart libraries [1, 2]. D ata annotation on our recent finding allows us to construct the profiles of genes in the energy metabolizing pathways (glycolysis and glycogen metabol ism) that are expressed in heart cDNA libraries. In silico studies of genes of energy metabolism yields data that are consistent with results derived from conventional metabolic experiments. The change in gene profiles descri bing the metabolism of diseased hearts is also presented here.