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 necessary. We have used single-pass sequencing of randomly selected cDNA clones to generate expressed sequence tags (ESTs). These ESTs data has been widely used to study gene expression in a variety of heart libraries [1, 21]. Data annotation on our recent finding allows us to construct the profiles of genes in the energy metabolizing pathways (glycolysis and glycogen metabolism) 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 describing the metabolism of diseased hearts is also presented here.
Ngai
S M
SM
Department of Biochemistry, The Chinese University of Hong Kong, Shatin, N.T., Special Administrative Region.
Way
M M
MM
Chan
H
H
Tsui
S K
SK
Lee
C Y
CY
Fung
K P
KP
D006332:Cardiomegaly / Q000235:genetics / Q000378:metabolism; D009202:Cardiomyopathies / Q000235:genetics / Q000378:metabolism; D019295:Computational Biology / Q000379:methods*; D004734:Energy Metabolism / Q000235:genetics*; D020224:Expressed Sequence Tags; D005786:Gene Expression Regulation; D015723:Gene Library; D005947:Glucose / Q000378:metabolism; D006003:Glycogen / Q000378:metabolism; D006019:Glycolysis / Q000235:genetics; D006321:Heart / Q000196:embryology / Q000502:physiology*; D006801:Humans; D019289:Pyruvic Acid / Q000378:metabolism
D019289:Pyruvic Acid; D006003:Glycogen; D005947:Glucose