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
10 papers · 1 filter
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 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…
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…
Aligning biological sequences by exploiting residue conservation and coevolution
Anna Paola Muntoni, Andrea Pagnani, Martin Weigt +1
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 alignme…
Initial cell density encodes proliferative potential in cancer cell populations
Chiara Enrico Bena, Marco Del Giudice, Alice Grob +8
Individual cells exhibit specific proliferative responses to changes in microenvironmental conditions. Whether such potential is constrained by the cell density throughout the grow…
Simultaneous identification of specifically interacting paralogs and inter-protein contacts by Direct-Coupling Analysis
Thomas Gueudré, Carlo Baldassi, Marco Zamparo +2
Understanding protein-protein interactions is central to our understanding of almost all complex biological processes. Computational tools exploiting rapidly growing genomic databa…
Inter-protein sequence co-evolution predicts known physical interactions in bacterial ribosomes and the trp operon
Christoph Feinauer, Hendrik Szurmant, Martin Weigt +1
Interaction between proteins is a fundamental mechanism that underlies virtually all biological processes. Many important interactions are conserved across a large variety of speci…
Fast and accurate multivariate Gaussian modeling of protein families: Predicting residue contacts and protein-interaction partners
Carlo Baldassi, Marco Zamparo, Christoph Feinauer +4
In the course of evolution, proteins show a remarkable conservation of their three-dimensional structure and their biological function, leading to strong evolutionary constraints o…
Bayesian inference of epidemics on networks via Belief Propagation
Fabrizio Altarelli, Alfredo Braunstein, Luca Dall'Asta +2
We study several bayesian inference problems for irreversible stochastic epidemic models on networks from a statistical physics viewpoint. We derive equations which allow to accura…
Direct-coupling analysis of residue co-evolution captures native contacts across many protein families
Faruck Morcos, Andrea Pagnani, Bryan Lunt +7
The similarity in the three-dimensional structures of homologous proteins imposes strong constraints on their sequence variability. It has long been suggested that the resulting co…