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WebGimm:一个基于网络的集成平台,用于聚类分析、功能分析和结果的交互式可视化。

WebGimm: An integrated web-based platform for cluster analysis, functional analysis, and interactive visualization of results.

作者信息

Joshi Vineet K, Freudenberg Johannes M, Hu Zhen, Medvedovic Mario

机构信息

Laboratory for Statistical Genomics and Systems Biology, Department of Environmental Health, University of Cincinnati College of Medicine, 3223 Eden Av, ML 56, Cincinnati OH 45267-0056, USA.

出版信息

Source Code Biol Med. 2011 Jan 17;6:3. doi: 10.1186/1751-0473-6-3.

Abstract

Cluster analysis methods have been extensively researched, but the adoption of new methods is often hindered by technical barriers in their implementation and use. WebGimm is a free cluster analysis web-service, and an open source general purpose clustering web-server infrastructure designed to facilitate easy deployment of integrated cluster analysis servers based on clustering and functional annotation algorithms implemented in R. Integrated functional analyses and interactive browsing of both, clustering structure and functional annotations provides a complete analytical environment for cluster analysis and interpretation of results. The Java Web Start client-based interface is modeled after the familiar cluster/treeview packages making its use intuitive to a wide array of biomedical researchers. For biomedical researchers, WebGimm provides an avenue to access state of the art clustering procedures. For Bioinformatics methods developers, WebGimm offers a convenient avenue to deploy their newly developed clustering methods. WebGimm server, software and manuals can be freely accessed at http://ClusterAnalysis.org/.

摘要

聚类分析方法已得到广泛研究,但新方法的采用往往受到其实施和使用中的技术障碍的阻碍。WebGimm是一个免费的聚类分析网络服务,也是一个开源的通用聚类网络服务器基础设施,旨在促进基于R中实现的聚类和功能注释算法的集成聚类分析服务器的轻松部署。集成的功能分析以及对聚类结构和功能注释的交互式浏览为聚类分析和结果解释提供了一个完整的分析环境。基于Java Web Start客户端的界面以熟悉的聚类/树视图包为模型,使其对广大生物医学研究人员来说易于使用。对于生物医学研究人员,WebGimm提供了一条途径来访问最先进的聚类程序。对于生物信息学方法开发者,WebGimm提供了一条方便的途径来部署他们新开发的聚类方法。可通过http://ClusterAnalysis.org/免费访问WebGimm服务器、软件和手册。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1ec2/3033799/a0cdf20210c1/1751-0473-6-3-1.jpg

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