Introduction

"The completion of a high-quality, comprehensive sequence of the human genome, in this fiftieth anniversary year of the discovery of the double-helical structure of DNA, is a landmark event. The genome era is now a reality ... and a revolution in biological research has begun" (1). Undoubtedly, the unprecedented explosion of datasets (including genomes, transcriptomes, proteomes, allelic variability, mapping, synteny, mutational data, and various model organism genetic and phenotypic datasets) and tools (database interfaces and analysis software) has transformed biomedical research, drug discovery, and medical product development. Oncogenomics or cancer genomics, the application of genomics to understand, diagnose, and combat cancer, is no exception and has been making significant advances. For example, genome-scale profiling of gene expression in tumor samples has provided new insights into the molecular characterization of many types of cancer. Microarray technology and other genomic approaches including genotyping by analysis of single-nucleotide polymorphisms (SNPs) hold the promise of enabling us to systematically profile individuals' genomes, making it possible to personalize cancer diagnosis and treatment. Because cancer is fundamentally a genetic disease occurring as a result of mutations in the genome, it is anticipated that genomics will play a critical role in cancer research and medicine.

Despite all of the publicity about the new "genome era" and the great opportunities that have arisen, many biomedical researchers are still largely unaware of what these datasets and tools can do for them and of how to best use them (2). The paradox arises because the new high-volume data now seem to be most useful only to specialists rather than to the larger research community. This problem will only become worse as the complexity of these databases continues to grow. The huge popular attention garnered by the Human Genome Project does have the beneficial effects of motivating and accelerating progress in the areas of genome sequencing, assembly, and annotation, aiming at turning the massive volumes of data into useful (and sometimes marketable) information. Nevertheless, the intense competition has also produced some undesirable results and hampered the use of these genomics resources (3).

In order to assist bench scientists to navigate these rapidly growing genomic resources, human genome resource guides, including the hands-on guide from Nature Genetics (4), the NCBI human genome resource fact sheets (http://www.nlm.nih.gov/pubs/factsheets/ humangenome.html), the NCBI information project handbook (http://www.ncbi.nlm.nih. gov/books/bv.fcgi?call=bv.View..ShowSection&rid=handbook), and resources describing the various database collections (5,6) have been developed and are freely accessible through the Internet.

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