In this paper, we research the community deception problem. Tackling this problem consists
in developing techniques to hide a target community (C) from community detection …

Motivation Biological networks topology yields important insights into biological function,
occurrence of diseases and drug design. In the last few years, different types of topological …

We present here a compact overview of the data, models and methods proposed for the
analysis of biological networks based on the search for significant repetitions. In particular …

Abstract Knowledge graphs may be successfully applied to represent different types of
relationships among different types of subjects. Here, we propose a Knowledge Graph …

This paper introduces the Better Hide Communities (BHC) benchmark dataset aimed at
standardizing evaluations in community deception across networks. BHC addresses the …

Protein–protein interaction networks have been broadly studied in the last few years, in
order to understand the behavior of proteins inside the cell. Proteins interacting with each …

Research in systems biology has made available large amounts of data about interactions
among cell building blocks (eg, proteins, genes). To properly look up these data and mine …

Motivation: Recent technological advances in measuring molecular interactions have
resulted in an increasing number of large-scale biological networks. Translation of these …

In recent years, extracting information from biological data has become a particularly
valuable way of gaining knowledge. Molecular interaction networks provide a framework for …

This paper introduces the Better Hide Communities (BHC) benchmark dataset, purposefully
crafted for gauging the efficacy of current and prospective community deception algorithms …