Department of Clinical Biochemistry & Pharmacology, Ben-Gurion University of the Negev, Beer-Sheva 84105, Israel.
Nucleic Acids Res. 2013 Jul;41(Web Server issue):W198-203. doi: 10.1093/nar/gkt532. Epub 2013 Jun 12.
Genome sequencing and transcriptomic profiling are two widely used approaches for the identification of human disease pathways. However, each approach typically provides a limited view of disease pathways: Genome sequencing can identify disease-related mutations but rarely reveals their mode-of-action, while transcriptomic assays do not reveal the series of events that lead to the transcriptomic change. ResponseNet is an integrative network-optimization approach that we developed to fill these gaps by highlighting major signaling and regulatory molecular interaction paths that connect disease-related mutations and genes. The ResponseNet web-server provides a user-friendly interface to ResponseNet. Specifically, users can upload weighted lists of proteins and genes and obtain a sparse, weighted, molecular interaction subnetwork connecting them, that is biased toward regulatory and signaling pathways. ResponseNet2.0 enhances the functionality of the ResponseNet web-server in two important ways. First, it supports analysis of human data by offering a human interactome composed of proteins, genes and micro-RNAs. Second, it offers a new informative view of the output, including a randomization analysis, to help users assess the biological relevance of the output subnetwork. ResponseNet2.0 is available at http://netbio.bgu.ac.il/respnet .
基因组测序和转录组谱分析是两种常用于识别人类疾病途径的方法。然而,每种方法通常只能提供疾病途径的有限视角:基因组测序可以识别与疾病相关的突变,但很少揭示其作用模式,而转录组分析并不能揭示导致转录组变化的一系列事件。ResponseNet 是一种整合的网络优化方法,我们开发它是为了通过突出连接疾病相关突变和基因的主要信号和调节分子相互作用路径来填补这些空白。ResponseNet 网络服务器提供了一个用户友好的界面来访问 ResponseNet。具体来说,用户可以上传加权的蛋白质和基因列表,并获得连接它们的稀疏、加权的分子相互作用子网络,该网络偏向于调节和信号通路。ResponseNet2.0 通过两种重要方式增强了 ResponseNet 网络服务器的功能。首先,它通过提供由蛋白质、基因和 microRNA 组成的人类相互作用组,支持人类数据的分析。其次,它提供了输出的新的信息视图,包括随机化分析,以帮助用户评估输出子网的生物学相关性。ResponseNet2.0 可在 http://netbio.bgu.ac.il/respnet 获得。