Volinia Stefano, Evangelisti Rita, Francioso Francesca, Arcelli Diego, Carella Massimo, Gasparini Paolo
Laboratory of Functional Genomics and Telethon Facility-Data Mining for Analysis of DNA Microarrays, Department of Morphology and Embryology, Università degli Studi, Via Fossato di Mortara 64/b, 44100 Ferrara, Italy.
Nucleic Acids Res. 2004 Jul 1;32(Web Server issue):W492-9. doi: 10.1093/nar/gkh443.
One of the most common problems encountered while deciphering results from expression profiling experiments is in relating differential expression of genes to molecular functions and cellular processes. A second important problem is that of comparing experiments performed by different labs using different microarray platforms, or even unrelated techniques. Gene Ontology (GO) is now used to describe biological features, since GO terms are associated with genes, to overcome the apparent distance between expression profiles and biological comprehension. Here we describe the development, implementation and use of GOAL (Gene Ontology Automated Lexicon), a web-based application for the identification of functions and processes regulated in microarray and SAGE (serial analysis of gene expression) experiments. We applied GOAL to a range of experimental datasets related to different biological problems, including cancer and the cell cycle. By using GOAL, reported and novel relevant processes were identified in a number of experiments by our collaborators and by us. Different datasets could also be compared with each other to define conserved functional modules. GOAL allows a seamless and high-level analysis of expression profiles and is implemented as a free WWW resource (http://microarrays.unife.it).
在解读表达谱实验结果时遇到的最常见问题之一,是将基因的差异表达与分子功能和细胞过程联系起来。另一个重要问题是比较不同实验室使用不同微阵列平台甚至不相关技术所进行的实验。基因本体论(GO)现在被用于描述生物学特征,因为GO术语与基因相关联,以克服表达谱与生物学理解之间明显的差距。在这里,我们描述了GOAL(基因本体论自动词典)的开发、实施和使用,这是一个基于网络的应用程序,用于识别在微阵列和SAGE(基因表达序列分析)实验中受调控的功能和过程。我们将GOAL应用于一系列与不同生物学问题相关的实验数据集,包括癌症和细胞周期。通过使用GOAL,我们的合作者和我们在许多实验中识别出了已报道的和新的相关过程。不同的数据集也可以相互比较以定义保守的功能模块。GOAL允许对表达谱进行无缝且高级的分析,并作为一个免费的万维网资源(http://microarrays.unife.it)来实现。