Network data has become widespread, larger, and more complex over the years. Traditional
network data is dyadic, capturing the relations among pairs of entities. With the need to …

Network motifs are recurrent and over‐represented patterns having biological relevance.
This is one of the important local properties of biological networks. Network motif discovery …

In the toxicological testing of new small-molecule compounds, it is desirable to establish in
silico test methods to predict toxicity instead of relying on animal testing. Since quantitative …

Modern cyber-physical systems must exhibit high reliability since their failures can lead to
catastrophic cascading events. Enhancing our understanding of the mechanisms behind the …

Measuring the dissimilarities between networks is a basic problem and wildly used in many
fields. Based on method of the D-measure which is suggested for unweighted networks, we …

Mechanism isomorphism identification is a typical quadratic assignment problem similar to
traveling salesman and job-shop scheduling. For the complex mechanism with more …

Network motif identification problem aims to find topological patterns in biological networks.
Identifying disjoint motifs is a computationally challenging problem using classical …

Mathematical model simulation is a useful method for understanding the complex behavior
of a living system. The construction of mathematical models using comprehensive …

Biological networks are powerful representations of topological features in biological
systems. Finding network motifs in biological networks is a computationally hard problem …

Learning and memory formation in living organisms is an issue under investigation. How
learning occurs is not fully understood. Nevertheless, learning and memory are evaluated to …