Simple graph algorithms such as PageRank have been the target of numerous hardware
accelerators. Yet, there also exist much more complex graph mining algorithms for problems …

We modify an algorithm of Bron and Kerbosch [1973] for maximal clique enumeration to
choose more carefully the order in which the vertices are processed, giving us a fixed …

Delineating the tremendous growth in this area, the Handbook of Approximation Algorithms
and Metaheuristics covers fundamental, theoretical topics as well as advanced, practical …

Background Most proteins form macromolecular complexes to perform their biological
functions. However, experimentally determined protein complex data, especially of those …

The problem of maximal clique enumeration (MCE) is to enumerate all of the maximal
cliques in a graph. Once enumerated, maximal cliques are widely used to solve problems in …

In recent years, machine learning (ML) has been revolutionizing biology, biomedical
sciences, and gene‐based agricultural technology capabilities. Massive data generated in …

Motivation: Recent improvements in high-throughput Mass Spectrometry (MS) technology
have expedited genome-wide discovery of protein–protein interactions by providing a …

We propose a geometric scattering-based graph neural network (GNN) for approximating
solutions of the NP-hard maximum clique (MC) problem. We construct a loss function with …

Citation behaviour is the source driver of scientific dynamics, and it is essential to
understand its effect on knowledge diffusion and intellectual structure. This study explores …

We propose GraphMineSuite (GMS): the first benchmarking suite for graph mining that
facilitates evaluating and constructing high-performance graph mining algorithms. First …