Dieterich Guido, Kärst Uwe, Wehland Jürgen, Jänsch Lothar
Department of Cell Biology, Research Centre for Biotechnology (GBF), Mascheroder Weg 1, 38124 Braunschweig, Germany.
Bioinformatics. 2006 Mar 1;22(5):630-1. doi: 10.1093/bioinformatics/bti814. Epub 2005 Dec 8.
The visualization-aided exploration of complex datasets will allow the research community to formulate novel functional hypotheses leading to a better understanding of biological processes at all levels. Therefore, we have developed a web resource termed VIS-O-BAC designed for the functional investigation of expression data for model systems, such as bacterial pathogens based on a graphical display. Genome-scale datasets derived from typical 'omic' approaches can directly be explored with respect to three biologically relevant aspects, the genome structure (operon organization), the organization of genes in pathways (KEGG) and the gene function with Gene Ontology (GO) terms. The integrated viewers can be used in parallel and combine expression data and functional annotations from different external data repositories. The graphical visualizations evidently accelerate both the validation of regulatory information and the detection of affected biological processes.
http://leger2.gbf.de/cgi-bin/vis-o-bac.pl.
Supplementary data are available at Bioinformatics online.
对复杂数据集进行可视化辅助探索将使研究界能够提出新的功能假设,从而更好地理解各个层面的生物过程。因此,我们开发了一个名为VIS-O-BAC的网络资源,用于基于图形显示对模型系统(如细菌病原体)的表达数据进行功能研究。从典型的“组学”方法获得的基因组规模数据集可以直接从三个生物学相关方面进行探索,即基因组结构(操纵子组织)、通路中的基因组织(KEGG)以及使用基因本体(GO)术语的基因功能。集成查看器可以并行使用,并结合来自不同外部数据存储库的表达数据和功能注释。图形可视化明显加快了调控信息的验证和受影响生物过程的检测。
http://leger2.gbf.de/cgi-bin/vis-o-bac.pl。
补充数据可在《生物信息学》在线获取。