Mining expressed sequence tag (EST) libraries for cancer-associated genes.
Originally established in the beginning of the 1990s as a direct route to gene finding, expressed sequence tags (ESTs) still lend themselves as a means to analyze gene expression in almost all human tissues. The type of questions that can be addressed using public EST libraries ranges from tissue-specific gene profiling to the comparison between tissues in diseased and healthy states. Thanks to a multitude of web-based online bioinformatics resources, mining in EST libraries is not restricted to experts in the field of data analysis, but can readily be performed by the medical or life scientist. In this chapter, a couple of cases studies are presented that guide the scientist to the most useful online resources so that they can conduct their own research.
Schmitt
Armin O
AO
Institute for Animal Sciences, Humboldt-Universität zu Berlin, Berlin, Germany.
D019295:Computational Biology / Q000379:methods*; D018076:DNA, Complementary / Q000378:metabolism; D057225:Data Mining; D030541:Databases, Genetic; D020224:Expressed Sequence Tags; D020869:Gene Expression Profiling; D015972:Gene Expression Regulation, Neoplastic; D015723:Gene Library; D052138:Genes, Neoplasm; D006801:Humans; D020407:Internet; D008967:Molecular Biology / Q000379:methods; D009369:Neoplasms / Q000235:genetics*; D020411:Oligonucleotide Array Sequence Analysis
D018076:DNA, Complementary