36 citations · 180 across the 14 of their papers we have counts for
14 papers
adabmDCA 2.0 -- a flexible but easy-to-use package for Direct Coupling Analysis
Lorenzo Rosset, Roberto Netti, Anna Paola Muntoni +2
In this methods article, we provide a flexible but easy-to-use implementation of Direct Coupling Analysis (DCA) based on Boltzmann machine learning, together with a tutorial on how…
Effectiveness of probabilistic contact tracing in epidemic containment: the role of super-spreaders and transmission path reconstruction
A. P. Muntoni, F. Mazza, A. Braunstein +2
The recent COVID-19 pandemic underscores the significance of early-stage non-pharmacological intervention strategies. The widespread use of masks and the systematic implementation…
DCAlign v1.0: Aligning biological sequences using co-evolution models and informed priors
Anna Paola Muntoni, Andrea Pagnani
DCAlign is a new alignment method able to cope with the conservation and the co-evolution signals that characterize the columns of multiple sequence alignments of homologous sequen…
Inference in conditioned dynamics through causality restoration
Alfredo Braunstein, Giovanni Catania, Luca Dall'Asta +2
Computing observables from conditioned dynamics is typically computationally hard, because, although obtaining independent samples efficiently from the unconditioned dynamics is us…
adabmDCA: Adaptive Boltzmann machine learning for biological sequences
Anna Paola Muntoni, Andrea Pagnani, Martin Weigt +1
Boltzmann machines are energy-based models that have been shown to provide an accurate statistical description of domains of evolutionary-related protein and RNA families. They are…
Relationship between fitness and heterogeneity in exponentially growing microbial populations
Anna Paola Muntoni, Alfredo Braunstein, Andrea Pagnani +2
Despite major environmental and genetic differences, microbial metabolic networks are known to generate consistent physiological outcomes across vastly different organisms. This re…