Applications of clustering algorithms in biomedical research are ubiquitous, with typical
examples including gene expression data analysis, genomic sequence analysis, biomedical …

Network modeling has proven to be a fundamental tool in analyzing the inner workings of a
cell. It has revolutionized our understanding of biological processes and made significant …

Background Data clustering analysis has been extensively applied to extract information
from gene expression profiles obtained with DNA microarrays. To this aim, existing …

Clustering is a commonly used method for exploring and analysing data where the primary
objective is to categorise observations into similar clusters. In recent decades, several …

Many clustering techniques have been proposed for the analysis of gene expression data
obtained from microarray experiments. However, choice of suitable method (s) for a given …

Microarray experiments monitor the expression of genes over a set of samples or
experimental conditions. Clustering approaches focused on this genomic information …

Evolutionary clustering algorithms have considered as the most popular and widely used
evolutionary algorithms for minimising optimisation and practical problems in nearly all …

Background The availability of microarrays measuring thousands of genes simultaneously
across hundreds of biological conditions represents an opportunity to understand both …

To enable safe and efficient use of multi-robot systems in everyday life, a robust and fast
method for coordinating their actions must be developed. In this paper, we present a …

Open source projects do have requirements; they are, however, mostly informal, text
descriptions found in requests, forums, and other correspondence. Understanding of such …