36 citations · 180 across the 14 of their papers we have counts for
4 papers · 1 filter
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…
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…
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…