Department of Genetics, Faculty of Medicine, University of São Paulo, Ribeirão Preto, Brazil.
BMC Bioinformatics. 2010 Mar 30;11:161. doi: 10.1186/1471-2105-11-161.
The post-genomic era has brought new challenges regarding the understanding of the organization and function of the human genome. Many of these challenges are centered on the meaning of differential gene regulation under distinct biological conditions and can be performed by analyzing the Multiple Differential Expression (MDE) of genes associated with normal and abnormal biological processes. Currently MDE analyses are limited to usual methods of differential expression initially designed for paired analysis.
We proposed a web platform named ProbFAST for MDE analysis which uses Bayesian inference to identify key genes that are intuitively prioritized by means of probabilities. A simulated study revealed that our method gives a better performance when compared to other approaches and when applied to public expression data, we demonstrated its flexibility to obtain relevant genes biologically associated with normal and abnormal biological processes.
ProbFAST is a free accessible web-based application that enables MDE analysis on a global scale. It offers an efficient methodological approach for MDE analysis of a set of genes that are turned on and off related to functional information during the evolution of a tumor or tissue differentiation. ProbFAST server can be accessed at http://gdm.fmrp.usp.br/probfast.
后基因组时代带来了新的挑战，需要理解人类基因组的组织和功能。这些挑战的核心是分析与正常和异常生物过程相关的基因的多重差异表达 (MDE)，以了解不同生物条件下差异基因调控的意义。目前，MDE 分析仅限于最初为配对分析设计的常用差异表达方法。
我们提出了一个名为 ProbFAST 的网络平台，用于 MDE 分析，该平台使用贝叶斯推断来识别关键基因，并通过概率直观地对其进行优先级排序。一项模拟研究表明，与其他方法相比，我们的方法具有更好的性能，并且当应用于公共表达数据时，我们证明了它具有获得与正常和异常生物过程相关的生物学相关关键基因的灵活性。
ProbFAST 是一个免费的可访问的网络应用程序，能够在全球范围内进行 MDE 分析。它提供了一种有效的方法，用于分析与肿瘤或组织分化过程中的功能信息相关的一组基因的开启和关闭的 MDE。ProbFAST 服务器可在 http://gdm.fmrp.usp.br/probfast 访问。
