Cavallaro Sebastiano
Istituto di Scienze Neurologiche, CNR, Viale Regina Margherita 6, Catania, Italy.
Neuroinformatics. 2007 Summer;5(2):115-26. doi: 10.1007/s12021-007-0006-3.
Apoptosis is a key physiological response that occurs during development of the nervous system, resulting in the death of nearly half of the embryonic neuronal population. Aberrant apoptotic mechanisms are thought to contribute significantly to many neurological disorders including Alzheimer's disease. Although many experiments in the past have demonstrated the requirement of de novo gene expression during neuronal apoptosis, the complete spectrum of genes involved in distinct temporal domains is mostly unknown. To begin a comprehensive survey of the gene-based molecular mechanisms that underlie neuronal apoptosis, we have used the unprecedented experimental opportunities that genome sequences and the development of DNA microarray technology now provide to perform genome-wide expression analysis in different paradigms of neuronal apoptosis. In order to extract knowledge from gene expression information we have developed new informatics applications that enable clustering methods based on semantic characteristics, such as gene ontologies. This review will highlight the use of a genomic approach to identify the molecular program underlying neuronal apoptosis and illustrate how a semantic clustering method can be useful to extract more knowledge from microarray data.
细胞凋亡是神经系统发育过程中发生的一种关键生理反应,导致近一半的胚胎神经元群体死亡。异常的凋亡机制被认为是导致包括阿尔茨海默病在内的许多神经疾病的重要原因。尽管过去许多实验已经证明神经元凋亡过程中需要从头进行基因表达,但参与不同时间域的完整基因谱大多未知。为了全面研究神经元凋亡的基于基因的分子机制,我们利用了基因组序列和DNA微阵列技术发展所提供的前所未有的实验机会,在不同的神经元凋亡范式中进行全基因组表达分析。为了从基因表达信息中提取知识,我们开发了新的信息学应用程序,这些程序能够实现基于语义特征(如基因本体)的聚类方法。本综述将重点介绍使用基因组方法来识别神经元凋亡背后的分子程序,并说明语义聚类方法如何有助于从微阵列数据中提取更多知识。