Complex networks play a very important role in various fields of science as data structures,
which aggregate information about mutual relationships between numerous objects. The …

Motivations of the Trip The use of a graph-based pattern representation induces the need to
formulate the main operations required in Pattern Recognition in terms of operations on …

We revisit the effectiveness of topological descriptors for molecular graph classification and
design a simple, yet strong baseline. We demonstrate that a simple approach to feature …

We present a new method of quantitative graph analysis and visualization based on vertex
centrality measures and distance matrices. After generating distance k-graphs and collecting …

In this work, we introduce a novel graph embedding technique called NERO (Network
Embedding based on Relation Order histograms). Its performance is assessed using a …

We present the analysis of the topological graph descriptor Local Degree Profile (LDP),
which forms a widely used structural baseline for graph classification. Our study focuses on …

We present a new framework for analysis and visualization of complex networks based on
structural information retrieved from their distance k‐graphs and B‐matrices. The …

We discuss the components and main requirements of the interactive visualization and
simulation system intended for better understanding the dynamics of solid tumor …

Let $ G $ be a finite connected graph on two or more vertices and $ G^{[N, k]} $ the distance
$ k $-graph of the $ N $-fold Cartesian power of $ G $. For a fixed $ k\ge1 $, we obtain …

New folds of protein structures emerge in evolution as a result of insertions, deletions or
shuffling of fragments of underlying gene sequences, and from aggregated effects of point …