The human immunodeficiency virus (HIV) has a strong affinity towards CD4+ T cell, dendritic
cells and macrophages and is present in white blood cells of the human body, and …

Biclustering come in various algorithms, selecting the most suitable biclustering algorithm
can be a challenging task. The performance of algorithms can vary significantly depending …

Due to the rise of microarray technology, many tools and methods have been developed to
analyse the huge number of gene expression data such as clustering analysis. This …

Abstract Backgrounds: Dirichlet Bayesian network (DBN) model is a method with score-
based structural learning, leading to a more accurate knowledge of the structure of the …

En la literatura se han propuesto muchos esquemas y modelos de enrutamiento basados
en clustering en redes de sensores inalámbricas. El modelo propuesto en este trabajo …

Proteome-scale bioinformatics research is increasingly conducted as the number of
completely sequenced genomes increases, but analysis of protein domains (PDs) usually …

Cancer subtype information is significant to understand tumour heterogeneity. Present
methods to find cancer subtypes have focused on utilizing traditional clustering algorithms …

The analysis of biological data is a challenging problem in bioinformatics and data mining
field. Given the complexity of the analysis of biological information, several methods have …