FEATURE ARTICLE
Gene Chips and Functional Genomics
A new technology will allow environmental health scientists to track the expression of thousands of genes in a single, fast and easy test
Hisham Hamadeh, Cynthia Afshari
Complementing Genomic Resources
A subset of the spots plated onto a chip carrys known genes, but most microarray chips will contain a significant portion of unknown genes. The functions of many of these unknown genes may be revealed with the help of computing and bioinformatics resources. Much of the information generated is filed in large-scale public databases.
These databases are constantly updated with information such as the sequences of discovered genes, their current known function and their latest nomenclature. The National Center for Biotechnology Information (NCBI), a branch of the National Institutes of Health, creates public databases, conducts research in computational biology, develops software tools for analyzing genome data and disseminates biomedical information. An example of such a database is UniGene, which is an experimental system for automatically partitioning sequences in the larger GenBank database into a non-redundant set of gene-oriented clusters. Each UniGene "cluster" contains sequences that represent a unique gene, as well as related information, such as the tissue types in which the gene is expressed.
In addition to sequences of well-characterized genes, hundreds of thousands of novel expressed sequence tag (EST) sequences—sequences from genes that remain undidentified that are known only through their message—can be found in UniGene. This collection is an invaluable resource for microarray researchers, since a lot of the spots printed on chips are ESTs. Consequently, this resource facilitates the identification of a gene for which large-scale analysis indicates an involvement of some of the ESTs. Microarray users' results depend on these databases to ensure that their data reflect the latest updates on genes. This ultimately makes a microarray data set even more meaningful. In the near future, databases of expression profiles will be publicly available. These databases include information about the sample quality and conditions under which it was produced, hybridization conditions and quality, scanning quality and outlier lists. This database will be made available to all scientists interested in learning from the data. The database user or "virtual experimenter" will have information about many different compounds and their signature effects within the context of the defined biological model.
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