The computational or in silico approaches for analysing the HIV-1-human protein–protein
interaction (PPI) network, predicting different host cellular factors and PPIs and discovering …

Semi-supervised consensus clustering, also called semi-supervised ensemble clustering, is
a recently emerged technique that integrates prior knowledge into consensus clustering in …

Climate-change driven sea level rise causes a increase in salinity in coastal wetlands
accelerating the alteration of the species composition. It triggers the gradual extinction of …

Protein–protein interactions (PPIs) have been widely used to understand different biological
processes and cellular functions associated with several diseases like cancer. Although …

Biclustering has been very relevant within the field of gene expression data analysis. In fact,
its main thrust stands in its ability to identify groups of genes that behave in the same way …

The efficient discovery of frequent itemsets from a transaction database is the fundamental
step for association rule mining in data analytics. Interesting associations among the items …

In this paper, we present a novel fuzzy rule extraction approach by employing the Gaussian
kernels and fuzzy concept lattices. First we introduce the Gaussian kernel to interval type-2 …

A majority of existing biclustering algorithms for microarrays data focus only on extracting
biclusters with positive correlations of genes. Nevertheless, biological studies show that a …

Biclustering is a popular technique to study gene expression data, especially to identify
functionally related groups of genes under subsets of conditions. Nevertheless, most of the …

Pattern extraction is one of the major topics in the Knowledge Discovery from Data (KDD)
and Background Knowledge Integration (BKI) research domains. Extracting patterns from …