Fannon M R
Human Genome Sciences, Rockville, MD 20850, USA.
Trends Biotechnol. 1996 Aug;14(8):294-8. doi: 10.1016/0167-7799(96)10041-X.
Analysis of gene-expression patterns derived from large expressed sequence tag (EST) databases has become a valuable tool in the discovery of therapeutic targets and diagnostic markers. Sequence data derived from a wide variety of cDNA libraries offer a wealth of information for identifying genes for pharmaceutical product development. Collecting, storing, organizing, analyzing and presenting cDNA expression data requires advanced bioinformatics methods and high-performance computational equipment. Comparison of expression patterns from normal and disease tissues enables inferences about gene function to be made, and medically relevant genes as candidates for therapeutics research and development programs to be identified.
对源自大型表达序列标签(EST)数据库的基因表达模式进行分析,已成为发现治疗靶点和诊断标志物的一项重要工具。从各种各样的cDNA文库获得的序列数据,为识别用于医药产品开发的基因提供了丰富的信息。收集、存储、整理、分析和呈现cDNA表达数据需要先进的生物信息学方法和高性能的计算设备。比较正常组织和疾病组织的表达模式,有助于推断基因功能,并识别出作为治疗研究与开发项目候选对象的医学相关基因。