The analysis of temporal data has gained increasing attention in recent years, aiming to
identify patterns and trends that change over time. Temporal triclustering is a promising …

This work proposes a new class of explainable prognostic models for longitudinal data
classification using triclusters. A new temporally constrained triclustering algorithm, termed …

Background Three-way data started to gain popularity due to their increasing capacity to
describe inherently multivariate and temporal events, such as biological responses, social …

The development of statistically and biologically competent Community Detection Algorithm
(CDA) is essential for extracting hidden information from massive biological datasets. This …

Mining patterns of co-expressed genes across the subset of conditions help to narrow down
the search space for the analysis of gene expression data. Identifying conditions specific key …

Development of high-throughput technologies in molecular biology during the last two
decades has contributed to the production of tremendous amounts of data. Microarray and …

HIV-1 is a virus that destroys CD4+ cells in the body's immune system, causing a drastic
decline in immune system performance. Analysis of HIV-1 gene expression data is urgently …

The development of functionally enriched and biologically competent biclustering algorithm
is essential for extracting hidden information from massive biological datasets. This paper …

An extensive empirical study is presented in this work to identify potential biomarkers of
ESCC by employing fifteen prominent biclustering algorithms on synthetic and real datasets …

The presence of missing data in a dataset plays a vital role in the design of classification,
clustering, or regression methods. An efficient missing data imputation can enhance the …