Recently, biclustering is one of the hot topics in bioinformatics and takes the attention of authors from several different disciplines. Hence, many different methodologies from a variety of disciplines are proposed as a solution to the biclustering problem. As a consequence of this issue, a variety of solutions makes it harder to evaluate the proposed methods. With this review paper, we are aimed to discuss both analysis and visualization of biclustering as a guide for the comparisons between brand new and existing biclustering algorithms. Additionally, we concentrate on the tools that provide visualizations with accompanied analysis techniques. Through the paper, we give several references that are also a short review of the state of the art for the ones who will pursue research on biclustering. The Paper outline is as follows; we first give the visualization and analysis methods, then we evaluate each proposed tool with the visualization contribution and analysis options, finally, we discuss future directions for biclustering and we propose standards for future work.
翻译：最近,双集群是生物信息学的热题之一,引起了不同学科作者的注意。因此,提出了许多不同学科的不同方法,作为双集群问题的解决办法。由于这一问题,各种解决办法使得评估拟议方法更加困难。本审查文件的目的是讨论双集群的分析和可视化,作为品牌新式和现有双集群算法之间比较的指南。此外,我们集中关注提供可视化工具以及配套分析技术的工具。我们通过该文件提供若干参考,也简短地回顾将进行双集群研究的那些人的艺术状况。文件大纲如下:我们首先提供可视化和分析方法,然后我们用可视化贡献和分析选项评估每一项拟议工具,最后,我们讨论双集群的未来方向,并提出未来工作的标准。
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