It is time to apply biclustering: a comprehensive review of biclustering applications in biological and biomedical data.

ABSTRACT: Biclustering is a powerful data mining technique that allows clustering of rows and columns, simultaneously, in a matrix-format data set. It was first applied to gene expression data in 2000, aiming to identify co-expressed genes under a subset of all the conditions/samples. During the past 17 years, tens of biclustering algorithms and tools have been developed to enhance the ability to make sense out of large data sets generated in the wake of high-throughput omics technologies. These algorithms and tools have been applied to a wide variety of data types, including but not limited to, genomes, transcriptomes, exomes, epigenomes, phenomes and pharmacogenomes. However, there is still a considerable gap between biclustering methodology development and comprehensive data interpretation, mainl

SUBMITTER: Xie J 

PROVIDER: S-EPMC6931057 | biostudies-literature | 2019 Jul

REPOSITORIES: biostudies-literature