no code implementations • 4 Sep 2023 • 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 sequences.
no code implementations • 7 Oct 2022 • 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 characterizations between homologous sequences in different organisms.
1 code implementation • 9 Sep 2021 • Anna Paola Muntoni, Andrea Pagnani, Martin Weigt, Francesco Zamponi
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.
1 code implementation • 6 Apr 2021 • Anna Paola Muntoni, Alfredo Braunstein, Andrea Pagnani, Daniele De Martino, Andrea De Martino
The constrained optimization of evolutionarily-motivated objective functions like the growth rate has emerged as the key theoretical assumption for the study of bacterial metabolism.
no code implementations • 4 Mar 2021 • Jeanne Trinquier, Guido Uguzzoni, Andrea Pagnani, Francesco Zamponi, Martin Weigt
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 proteins deeply hidden in rapidly growing sequence databases.
no code implementations • 20 Sep 2020 • Alfredo Braunstein, Thomas Gueudré, Andrea Pagnani, Mirko Pieropan
Efficient feature selection from high-dimensional datasets is a very important challenge in many data-driven fields of science and engineering.
no code implementations • 18 May 2020 • Anna Paola Muntoni, Andrea Pagnani, Martin Weigt, Francesco Zamponi
Here, we present DCAlign, an efficient alignment algorithm based on an approximate message-passing strategy, which is able to overcome the limitations of profile models, to include coevolution among positions in a general way, and to be therefore universally applicable to protein- and RNA-sequence alignment without the need of using complementary structural information.
no code implementations • 10 Apr 2019 • Alfredo Braunstein, Anna Paola Muntoni, Andrea Pagnani, Mirko Pieropan
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.
no code implementations • 3 Mar 2014 • Christoph Feinauer, Marcin J. Skwark, Andrea Pagnani, Erik Aurell
Correlation patterns in multiple sequence alignments of homologous proteins can be exploited to infer information on the three-dimensional structure of their members.