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Since the structure of the DNA molecule was identified half a century ago, the complete genome sequence has been determined for 37 prokaryotes and several eukaryotes. With the exponential growth of genetic information, bioinformatics has attempted to predict gene locations and functions in cyberspace prior to experimental confirmation at the bench.
Many of the gene products of completely sequenced organisms are 'hypothetical' - they cannot be related to any previously characterized proteins - and so are of completely unknown function. Structural studies provide one means of obtaining functional information in these cases. A 'structural genomics' project has been initiated aimed at determining the structures of 50 hypothetical proteins from Haemophilus influenzae to gain an understanding of their function. Each stage of the project - target selection, protein production, crystallization, structure determination, and structure analysis - makes use of recent advances to streamline procedures. Early results from this and similar projects are encouraging in that some level of functional understanding can be deduced from experimentally solved structures.
Although function can be assigned to genome sequence by homology at a macroscopic level, this can be misleading in the absence of data on enzyme activities. Together, such data can reveal whether open reading frames are expressed, identify multienzyme function and point to 'orphan' function. Because of their small size and small genomes, the genome sequences of some Mycoplasma spp. are very amenable to detailed analyses.
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Genome-scale sequencing projects have provided the essential information required for the construction of entire genome chips or microarrays for RNA expression studies. The Arabidopsis and rice genomes have been sequenced and whole-genome oligonucleotide arrays are being manufactured. These should soon become available to researchers. Expression studies using genomic-scale expression arrays are providing us with a vast quantity of information at a rapid pace. The rate-limiting step in this type of experiments is not the data generation step but rather the data analysis component of experiments. We report improvements that should facilitate the analysis of Affymetrix Genechip expression data.
The burden that heart failure imposes on the health care systems of the developed world is substantial and increasing. This article reviews the world literature on the epidemiology of heart failure and discusses the key methodological issues for research in this field.
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