Encoding brain regions and their connections as a network of nodes and edges captures
many of the possible paths along which information can be transmitted as humans process …

Computer simulations are used very often to understand and solve practical problems in the
area of statistical physics and biophysics. With proper knowledge of classical mechanics …

Persistent homology is a mathematical method to quantify topological features of shapes,
such as connectivity. This study applied persistent homology to analyze fracture network …

In the last years complex networks tools contributed to provide insights on the structure of
research, through the study of collaboration, citation and co-occurrence networks. The …

Process calculi have been proved to be a powerful tool for describing biological processes.
They allowed us to study the folding process of RNAs and proteins and identify an …

Many interesting problems that we would like to treat using computational molecular
modeling are unfortunately too large to be considered by quantum mechanics (QM) …

Our understanding of a biological process is often held back by the entanglement of
interactions at its basis, since the relation between these local connections and the process …

In this study, we employed a novel method for prediction of (macro) molecular properties
using a swarm artificial neural network method as a machine learning approach. In this …

Process algebras and agent-based models have proven to be effective methods for studying
biologi-cal systems. Our research employs such techniques to investigate the behaviours …

To provide accurate predictions of different thermodynamic properties of the (bio) molecular
systems, such as free energy of hydration, pKa, binding energy, or quantum mechanical …