Biclustering is an unsupervised machine-learning technique that simultaneously clusters
rows and columns in a data matrix. Over the past two decades, the field of biclustering has …

Biclustering algorithm is an effective tool for processing gene expression datasets. There are
two kinds of data matrices, binary data and non-binary data, which are processed by …

Biological evolution is generally regarded as a stochastic or probabilistic process, per the
ideas of Darwin in the nineteenth century. Even if this is true at the meso-scale, it still may …

Data-driven methods used on structural magnetic resonance imaging (sMRI) have been
successful in predicting disease subtypes within a population of subjects. Biclustering is a …

The behavior of many diseases is still not well understood by researchers. Genome-Wide
Association (GWA) analyzes have recently become a popular approach to discovering the …

One of the important aims of analyzing single-cell RNA sequencing (scRNA-seq) data is to
discovery new cell subtypes by clustering. For the scRNA-seq data, it is obvious that lots of …

Pattern discovery and subspace clustering are pervasive tasks across biological,
biotechnological, and biomedical domains. Parallel coordinates plots and heatmaps are …

According to the report, billions of people are affected by floods as it is a natural hazard
caused by heavy rainfall or glacier melting. Floods occur when there is an overflow of water …

Data-driven methods used on structural magnetic resonance imaging (sMRI) have been
successful in predicting disease subtypes within a population of subjects. Biclustering is a …

Fig. 1. Visualization of clustering (a) and co-clustering (b) results on the same data matrix. In
(a), the rows of the matrix are ordered according to their cluster assignment; each cluster A …