Anna Paola Muntoni
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View article: adabmDCA 2.0 – a flexible but easy-to-use package for Direct Coupling Analysis
adabmDCA 2.0 – a flexible but easy-to-use package for Direct Coupling Analysis Open
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 to use it. The package adabmDCA 2.0 is available in differ…
View article: adabmDCA 2.0 -- a flexible but easy-to-use package for Direct Coupling Analysis
adabmDCA 2.0 -- a flexible but easy-to-use package for Direct Coupling Analysis Open
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 to use it. The package \texttt{adabmDCA 2.0} is available …
View article: Effectiveness of probabilistic contact tracing in epidemic containment: The role of superspreaders and transmission path reconstruction
Effectiveness of probabilistic contact tracing in epidemic containment: The role of superspreaders and transmission path reconstruction Open
The recent COVID-19 pandemic underscores the significance of early stage nonpharmacological intervention strategies. The widespread use of masks and the systematic implementation of contact tracing strategies provide a potentially equally …
View article: Effectiveness of probabilistic contact tracing in epidemic containment: the role of super-spreaders and transmission path reconstruction
Effectiveness of probabilistic contact tracing in epidemic containment: the role of super-spreaders and transmission path reconstruction Open
The recent COVID-19 pandemic underscores the significance of early-stage non-pharmacological intervention strategies. The widespread use of masks and the systematic implementation of contact tracing strategies provide a potentially equally…
View article: DCAlign v1.0: aligning biological sequences using co-evolution models and informed priors
DCAlign v1.0: aligning biological sequences using co-evolution models and informed priors Open
Summary 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 sequences. However, the pre-processing steps required to …
View article: Optimal metabolic strategies for microbial growth in stationary random environments
Optimal metabolic strategies for microbial growth in stationary random environments Open
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 and metabolic degrees of freedom. In the standard sense, op…
View article: Inference in conditioned dynamics through causality restoration
Inference in conditioned dynamics through causality restoration Open
Estimating observables from conditioned dynamics is typically computationally hard. While obtaining independent samples efficiently from unconditioned dynamics is usually feasible, most of them do not satisfy the imposed conditions and mus…
View article: Optimal metabolic strategies for microbial growth in stationary random environments
Optimal metabolic strategies for microbial growth in stationary random environments Open
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 and metabolic degrees of freedom. In the standard sense, op…
View article: Inference in conditioned dynamics through causality restoration
Inference in conditioned dynamics through causality restoration Open
Computing observables from conditioned dynamics is typically computationally hard, because, although obtaining independent samples efficiently from the unconditioned dynamics is usually feasible, generally most of the samples must be disca…
View article: DCAlign v1.0: Aligning biological sequences using co-evolution models and informative priors
DCAlign v1.0: Aligning biological sequences using co-evolution models and informative priors Open
Summary DCAlign is a new alignment method able to cope with the conservation and the co-evolution signals that characterize the columns of a multiple sequence alignment of homologous sequences. However, the pre-processing steps required to…
View article: Sparse generative modeling via parameter reduction of Boltzmann machines: Application to protein-sequence families
Sparse generative modeling via parameter reduction of Boltzmann machines: Application to protein-sequence families Open
Boltzmann machines (BMs) are widely used as generative models. For example, pairwise Potts models (PMs), which are instances of the BM class, provide accurate statistical models of families of evolutionarily related protein sequences. Thei…
View article: Epidemic mitigation by statistical inference from contact tracing data
Epidemic mitigation by statistical inference from contact tracing data Open
Significance Contact tracing mobile applications are clear candidates for enabling us to slow down an epidemic and keep society running while holding the health risks down. Currently used mobile applications aim to notify individuals who w…
View article: A density consistency approach to the inverse Ising problem
A density consistency approach to the inverse Ising problem Open
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 and external fields) maximizing the likelihood of given empi…
View article: Aligning biological sequences by exploiting residue conservation and coevolution
Aligning biological sequences by exploiting residue conservation and coevolution Open
Sequences of nucleotides (for DNA and RNA) or amino acids (for proteins) are central objects in biology. Among the most important computational problems is that of sequence alignment, i.e., arranging sequences from different organisms in s…
View article: Unbiased metabolic flux inference through combined thermodynamic and<sup>13</sup>C flux analysis
Unbiased metabolic flux inference through combined thermodynamic and<sup>13</sup>C flux analysis Open
Quantification of cellular metabolic fluxes, for instance with 13 C-metabolic flux analysis, is highly important for applied and fundamental metabolic research. A current challenge in 13 C-flux analysis is that the available experimental d…
View article: Aligning biological sequences by exploiting residue conservation and coevolution
Aligning biological sequences by exploiting residue conservation and coevolution Open
Aligning biological sequences belongs to the most important problems in computational sequence analysis; it allows for detecting evolutionary relationships between sequences and for predicting biomolecular structure and function. Typically…
View article: Nonconvex image reconstruction via expectation propagation
Nonconvex image reconstruction via expectation propagation Open
The problem of efficiently reconstructing tomographic images can be mapped into a Bayesian inference problem over the space of pixels densities. Solutions to this problem are given by pixels assignments that are compatible with tomographic…
View article: Compressed sensing reconstruction using expectation propagation
Compressed sensing reconstruction using expectation propagation Open
Many interesting problems in fields ranging from telecommunications to computational biology can be formalized in terms of large underdetermined systems of linear equations with additional constraints or regularizers. One of the most studi…
View article: Statistical mechanics approaches to optimization and inference
Statistical mechanics approaches to optimization and inference Open
Nowadays, typical methodologies employed in statistical physics are successfully applied to a huge set of problems arising from different research fields. In this thesis I will propose several statistical mechanics based models able to dea…
View article: Practical optimization of Steiner trees via the cavity method
Practical optimization of Steiner trees via the cavity method Open
The optimization version of the cavity method for single instances, called\nMax-Sum, has been applied in the past to the Minimum Steiner Tree Problem on\nGraphs and variants. Max-Sum has been shown experimentally to give\nasymptotically op…