Noordewier M O, Warren P V
Department Bioinformatics, GlaxoSmithKline Pharmaceuticals, 1250 South Collegeville Rd, UP 1345, PO Box 5089, Collegeville, PA 19426, USA.
Trends Biotechnol. 2001 Oct;19(10):412-5. doi: 10.1016/S0167-7799(01)01735-8.
Large-scale parallel measurement of whole-genome RNA expression is now possible with high-density arrays of cDNA or oligonucleotides. Using this technology efficiently will require the integration of other sources of biological information, such as gene identity, biomedical literature and biochemical pathway for a given gene. Such integration is essential to understand the cellular program of gene expression and the molecular physiology of an organism. Advances in microarray technology, and the expected rapid rise in microarray data will lead to new insight into fundamental biological problems such as the prediction of gene function from expression profiles and the identification of potential drug targets from biologically active compounds.
利用高密度的cDNA或寡核苷酸阵列，现在可以对全基因组RNA表达进行大规模平行测量。要有效地使用这项技术，就需要整合其他生物信息来源，比如给定基因的基因身份、生物医学文献和生化途径。这种整合对于理解基因表达的细胞程序和生物体的分子生理学至关重要。微阵列技术的进步以及微阵列数据预计的快速增长，将为一些基本生物学问题带来新的见解，比如从表达谱预测基因功能以及从生物活性化合物中识别潜在药物靶点。
