Drozdov Ignat, Ouzounis Christos A, Shah Ajay M, Tsoka Sophia
Cardiovascular Division - King's College London (KCL) BHF Centre of Research Excellence - School of Medicine - James Black Centre - 125 Coldharbour Lane, London SE5 9NU - UK.
BMC Res Notes. 2011 Oct 28;4:462. doi: 10.1186/1756-0500-4-462.
Cellular constituents such as proteins, DNA, and RNA form a complex web of interactions that regulate biochemical homeostasis and determine the dynamic cellular response to external stimuli. It follows that detailed understanding of these patterns is critical for the assessment of fundamental processes in cell biology and pathology. Representation and analysis of cellular constituents through network principles is a promising and popular analytical avenue towards a deeper understanding of molecular mechanisms in a system-wide context.
We present Functional Genomics Assistant (FUGA) - an extensible and portable MATLAB toolbox for the inference of biological relationships, graph topology analysis, random network simulation, network clustering, and functional enrichment statistics. In contrast to conventional differential expression analysis of individual genes, FUGA offers a framework for the study of system-wide properties of biological networks and highlights putative molecular targets using concepts of systems biology.
FUGA offers a simple and customizable framework for network analysis in a variety of systems biology applications. It is freely available for individual or academic use at http://code.google.com/p/fuga.
蛋白质、DNA和RNA等细胞成分形成了一个复杂的相互作用网络,该网络调节生化稳态并决定细胞对外部刺激的动态反应。因此,详细了解这些模式对于评估细胞生物学和病理学中的基本过程至关重要。通过网络原理对细胞成分进行表示和分析是一种很有前景且广受欢迎的分析途径,有助于在全系统范围内更深入地理解分子机制。
我们展示了功能基因组学助手(FUGA)——一个可扩展且便携的MATLAB工具箱,用于推断生物关系、进行图拓扑分析、随机网络模拟、网络聚类以及功能富集统计。与传统的单个基因差异表达分析不同,FUGA提供了一个研究生物网络全系统特性的框架,并利用系统生物学概念突出潜在的分子靶点。
FUGA为各种系统生物学应用中的网络分析提供了一个简单且可定制的框架。它可在http://code.google.com/p/fuga上免费供个人或学术使用。