Authors :
Melih Sözdinler
Volume/Issue :
Volume 6 - 2021, Issue 12 - December
Google Scholar :
http://bitly.ws/gu88
Scribd :
https://bit.ly/3ECb11J
Abstract :
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.
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.
