Wiltgen Marco, Tilz Gernot P
Institute of Medical Informatics, Statistics and Documentation, Medical University of Graz, Graz, Austria.
Hematology. 2007 Aug;12(4):271-87. doi: 10.1080/10245330701283967.
In recent years, a new technology, allowing the measurements of the expression of thousands of genes simultaneously, has emerged in medicine. This method, called DNA microarray analysis, is today one of the most promising method in functional genomics. Fundamental patterns in gene expression are extracted by several clustering methods like: hierarchical clustering, self organizing maps and support vector machines. Changes in gene expression, as a response to changing environment conditions, diseases, drug treatment or chemotherapy medications, can be detected allowing insights into the dynamic of the genome. Microarrays seem to be an important tool for diagnosis of diseases at a molecular level. Applications are for example the improvement of diagnosis and treatment of cancer and the improvement of the effectiveness of drug treatment. In this introductory paper, we present the principles of DNA microarray experiments, selected clustering methods for gene expression analysis and the impact to clinical research.
近年来,医学领域出现了一项新技术,它能够同时测量数千个基因的表达情况。这种方法被称为DNA微阵列分析,如今是功能基因组学中最具前景的方法之一。基因表达的基本模式可通过多种聚类方法提取,如层次聚类、自组织映射和支持向量机。作为对不断变化的环境条件、疾病、药物治疗或化疗药物的反应,基因表达的变化能够被检测到,从而有助于深入了解基因组的动态变化。微阵列似乎是在分子水平上诊断疾病的重要工具。其应用包括例如改善癌症的诊断和治疗以及提高药物治疗的效果。在这篇介绍性论文中,我们阐述了DNA微阵列实验的原理、用于基因表达分析的选定聚类方法以及对临床研究的影响。