Understanding the underlying information for interpreted data from raw data is currently a key challenge to Bioinformatics. This is essentially related to the current flood of raw data, aggregate information, and evolving knowledge arising from the study of gene expressions. For the analysis and understanding of that underlying information, biclustering takes the attention of authors from several different disciplines. As a result, hundreds of different variation of the biclustering problem has been introduced as a solution to biclustering problem. Although biclustering is well studied, there is still some gap for combined and interpreted visualizations methods. With this review paper, we are aimed to discuss the visualizationmethods of biclustering by comparing current the state of the art with each other. Additionally, we concentrate on the tools that provide visualizations. Through this paper, we first presentthe visualization methods. Then, we evaluate each proposed tools with the state of the art visualization options. Finally, we discuss future directions for biclustering visualization.