Three types of highly promising small RNA therapeutics, namely, small interfering RNAs
(siRNAs), microRNAs (miRNAs) and the RNA subtype of antisense oligonucleotides (ASOs) …

Effectively compressing and optimizing tensor networks requires reliable methods for fixing
the latent degrees of freedom of the tensors, known as the gauge. Here we introduce a new …

Belief propagation is a widely used message passing method for the solution of probabilistic
models on networks such as epidemic models, spin models, and Bayesian graphical …

Networks and network computations have become a primary mathematical tool for analyzing
the structure of many kinds of complex systems, ranging from the Internet and transportation …

With the hit of new pandemic threats, scientific frameworks are needed to understand the
unfolding of the epidemic. The use of mobile apps that are able to trace contacts is of utmost …

Hypergraphs capture the higher-order interactions in complex systems and always admit a
factor graph representation, consisting of a bipartite network of nodes and hyperedges. As …

Quantifying the differences between networks is a challenging and ever-present problem in
network science. In recent years, a multitude of diverse, ad hoc solutions to this problem …

Percolation is an emblematic model to assess the robustness of interconnected systems
when some of their components are corrupted. It is usually investigated in simple scenarios …

Hypergraph describes real-world networks widely because it captures pairwise and multiple
nodes' interactions. Various kinds of damages, such as network attacks, hardware …

Source inference aims at revealing the seed of the misinformation spreading on social
networks, and attracted great attention in the field of network science and cybersecurity …