Zobrazeno 1 - 10
of 257
pro vyhledávání: '"Pagnani, Andrea"'
Autor:
Muntoni, Anna Paola, Pagnani, Andrea
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 align a candidate s
Externí odkaz:
http://arxiv.org/abs/2309.01540
Autor:
Budzynski, Louise, Pagnani, Andrea
Publikováno v:
Phys. Rev. E 107, 044125, Published 25 April 2023
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. Typica
Externí odkaz:
http://arxiv.org/abs/2210.03463
This contribution focuses on the fascinating RNA molecule, its sequence-dependent folding driven by base-pairing interactions, the interplay between these interactions and natural evolution, and its multiple regulatory roles. The four of us have dug
Externí odkaz:
http://arxiv.org/abs/2207.13402
Autor:
Manigrasso, Francesco, Milazzo, Rosario, Russo, Alessandro Sebastian, Lamberti, Fabrizio, Strand, Fredrik, Pagnani, Andrea, Morra, Lia
Publikováno v:
In Medical Image Analysis January 2025 99
Publikováno v:
BMC Bioinformatics 22, 528 (2021)
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 parametrized in terms of local biases accounting for residue conserva
Externí odkaz:
http://arxiv.org/abs/2109.04105
Autor:
Muntoni, Anna Paola, Braunstein, Alfredo, Pagnani, Andrea, De Martino, Daniele, De Martino, Andrea
Despite major environmental and genetic differences, microbial metabolic networks are known to generate consistent physiological outcomes across vastly different organisms. This remarkable robustness suggests that, at least in bacteria, metabolic act
Externí odkaz:
http://arxiv.org/abs/2104.02594
Publikováno v:
Nature Communications 12, 5800 (2021)
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. Here we
Externí odkaz:
http://arxiv.org/abs/2103.03292
Autor:
Sesta, Luca1 (AUTHOR) lucasesta95@gmail.com, Pagnani, Andrea1,2,3 (AUTHOR), Fernandez-de-Cossio-Diaz, Jorge4 (AUTHOR), Uguzzoni, Guido2 (AUTHOR)
Publikováno v:
PLoS Computational Biology. 2/20/2024, Vol. 20 Issue 2, p1-16. 16p.
Publikováno v:
Phys. Rev. E 103, 043301 (2021)
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 inspired strategy that addresses the problem of sparse feature select
Externí odkaz:
http://arxiv.org/abs/2009.09545
Publikováno v:
Phys. Rev. E 102, 062409 (2020)
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 such a way to
Externí odkaz:
http://arxiv.org/abs/2005.08500