230 citations · 626 across the 8 of their papers we have counts for
9 papers
Disentangling Node Attributes from Graph Topology for Improved Generalizability in Link Prediction
Ayan Chatterjee, Robin Walters, Giulia Menichetti +1
Link prediction is a crucial task in graph machine learning with diverse applications. We explore the interplay between node attributes and graph topology and demonstrate that inco…
AI-Bind: Improving Binding Predictions for Novel Protein Targets and Ligands
Ayan Chatterjee, Robin Walters, Zohair Shafi +7
Identifying novel drug-target interactions (DTI) is a critical and rate limiting step in drug discovery. While deep learning models have been proposed to accelerate the identificat…
Network measures for protein folding state discrimination
Giulia Menichetti, Piero Fariselli, Daniel Remondini
Proteins fold using a two-state or multi-state kinetic mechanisms, but up to now there isn't a first-principle model to explain this different behaviour. We exploit the network pro…
Control of Multilayer Networks
Giulia Menichetti, Luca Dall'Asta, Ginestra Bianconi
The controllability of a network is a theoretical problem of relevance in a variety of contexts ranging from financial markets to the brain. Until now, network controllability has…
Emergent Complex Network Geometry
Zhihao Wu, Giulia Menichetti, Christoph Rahmede +1
Networks are mathematical structures that are universally used to describe a large variety of complex systems such as the brain or the Internet. Characterizing the geometrical prop…
Correlations between weights and overlap in ensembles of weighted multiplex networks
Giulia Menichetti, Daniel Remondini, Ginestra Bianconi
Multiplex networks describe a large number of systems ranging from social networks to the brain. These multilayer structure encode information in their structure. This information…
Network Controllability Is Determined by the Density of Low In-Degree and Out-Degree Nodes
Giulia Menichetti, Luca Dall'Asta, Ginestra Bianconi
The problem of controllability of the dynamical state of a network is central in network theory and has wide applications ranging from network medicine to financial markets. The dr…
Weighted Multiplex Networks
Giulia Menichetti, Daniel Remondini, Pietro Panzarasa +2
One of the most important challenges in network science is to quantify the information encoded in complex network structures. Disentangling randomness from organizational principle…
Network Entropy measures applied to different systemic perturbations of cell basal state
G. Menichetti, G. Bianconi, E. Giampieri +2
We characterize different cell states, related to cancer and ageing phenotypes, by a measure of entropy of network ensembles, integrating gene expression values and protein interac…