1.6k citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Politecnico di TorinoIT83 papers
- Collegio Carlo AlbertoIT36 papers
- Istituto Nazionale di Fisica Nucleare, Sezione di TorinoIT27 papers
- Sapienza University of RomeIT21 papers
- Centre National de la Recherche ScientifiqueFR19 papers
- Istituto di NanotecnologiaIT19 papers
- National Research CouncilLK16 papers
- Sorbonne UniversitéFR14 papers
- Biologie Computationnelle, Quantitative et SynthétiqueFR12 papers
- École Normale Supérieure - PSLFR10 papers
- Institut de Biologie Paris-SeineFR9 papers
- Istituto Nazionale di Fisica NucleareIT9 papers
106 papers
Speed-quality tradeoff in a physical model of molecular sorting
Elisa Floris, Damiano Andreghetti, Thibaut Caplet +2
Eukaryotic cells rely on membrane-mediated processes to compartmentalize biomolecules, counteracting diffusion-driven homogenization. These processes involve the selective sorting…
Enzyme-driven phase separation
Damiano Andreghetti, Alfredo Braunstein, Luca Dall'Asta +1
The formation of polarized signaling domains on cell membranes is a fundamental example of biological pattern formation. While such patterns resemble structures from equilibrium ph…
Evidence of Replica Symmetry Breaking under the Nishimori conditions in epidemic inference on graphs
Alfredo Braunstein, Louise Budzynski, Matteo Mariani +1
In Bayesian inference, computing the posterior distribution from the data is typically a non-trivial problem, which usually requires approximations such as mean-field approaches or…
Nonequilibrium steady-state dynamics of Markov processes on graphs
Stefano Crotti, Thomas Barthel, Alfredo Braunstein
We propose an analytic approach for the steady-state dynamics of Markov processes on locally tree-like graphs. It is based on time-translation invariant probability distributions f…
Metabolic coordination and phase transitions in spatially distributed multi-cellular systems
Krishnadev Narayanankutty, José Antonio Pereiro-Morejon, Arián Ferrero-Fernández +7
During overflow metabolism, cells excrete glycolytic byproducts when growing under aerobic conditions in a seemingly wasteful fashion. While potentially advantageous for microbes w…
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…
Small-Coupling Dynamic Cavity: a Bayesian mean-field framework for epidemic inference
Alfredo Braunstein, Giovanni Catania, Luca Dall'Asta +3
We present the Small-Coupling Dynamic Cavity (SCDC) method, a novel generalized mean-field approximation for epidemic inference and risk assessment within a fully Bayesian framewor…
Statistical Mechanics of Inference in Epidemic Spreading
Alfredo Braunstein, Louise Budzynski, Matteo Mariani
We investigate the information-theoretical limits of inference tasks in epidemic spreading on graphs in the thermodynamic limit. The typical inference tasks consist in computing ob…
Matrix Product Belief Propagation for reweighted stochastic dynamics over graphs
Stefano Crotti, Alfredo Braunstein
Stochastic processes on graphs can describe a great variety of phenomena ranging from neural activity to epidemic spreading. While many existing methods can accurately describe typ…
A Survey on the Densest Subgraph Problem and Its Variants
Tommaso Lanciano, Atsushi Miyauchi, Adriano Fazzone +1
The Densest Subgraph Problem requires to find, in a given graph, a subset of vertices whose induced subgraph maximizes a measure of density. The problem has received a great deal o…
Sorting of multiple molecular species on cell membranes
A. Piras, E. Floris, L. Dall'Asta +1
Eukaryotic cells maintain their inner order by a hectic process of distillation of molecular factors taking place on the surface of their lipid membranes. To understand the propert…
Optimal metabolic strategies for microbial growth in stationary random environments
Anna Paola Muntoni, Andrea De Martino
In order to grow in any given environment, bacteria need to collect information about the medium composition and implement suitable growth strategies by adjusting their regulatory…
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…
Small Coupling Expansion for Multiple Sequence Alignment
Louise Budzynski, Andrea Pagnani
The alignment of biological sequences such as DNA, RNA, and proteins, is one of the basic tools that allow to detect evolutionary patterns, as well as functional/structural charact…
The closest vector problem and the zero-temperature p-spin landscape for lossy compression
Alfredo Braunstein, Louise Budzynski, Stefano Crotti +1
We consider a high-dimensional random constrained optimization problem in which a set of binary variables is subjected to a linear system of equations. The cost function is a simpl…
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…
Path-integral solution of MacArthur's resource-competition model for large ecosystems with random species-resources couplings
A. R. Batista-Tomas, Andrea De Martino, Roberto Mulet
We solve MacArthur's resource-competition model with random species-resource couplings in the `thermodynamic' limit of infinitely many species and resources using dynamical path-in…
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…
Efficient generative modeling of protein sequences using simple autoregressive models
Jeanne Trinquier, Guido Uguzzoni, Andrea Pagnani +2
Generative models emerge as promising candidates for novel sequence-data driven approaches to protein design, and for the extraction of structural and functional information about…
Sparse generative modeling via parameter-reduction of Boltzmann machines: application to protein-sequence families
Pierre Barrat-Charlaix, Anna Paola Muntoni, Kai Shimagaki +2
Boltzmann machines (BM) are widely used as generative models. For example, pairwise Potts models (PM), which are instances of the BM class, provide accurate statistical models of f…
A Density Consistency approach to the inverse Ising problem
Alfredo Braunstein, Giovanni Catania, Luca Dall'Asta +1
We propose a novel approach to the inverse Ising problem which employs the recently introduced Density Consistency approximation (DC) to determine the model parameters (couplings a…
Epidemic mitigation by statistical inference from contact tracing data
Antoine Baker, Indaco Biazzo, Alfredo Braunstein +10
Contact-tracing is an essential tool in order to mitigate the impact of pandemic such as the COVID-19. In order to achieve efficient and scalable contact-tracing in real time, digi…
Expectation propagation on the diluted Bayesian classifier
Alfredo Braunstein, Thomas Gueudré, Andrea Pagnani +1
Efficient feature selection from high-dimensional datasets is a very important challenge in many data-driven fields of science and engineering. We introduce a statistical mechanics…