Combining phylogeny and coevolution improves the inference of interaction partners among paralogous proteins.

Autor: Carlos A Gandarilla-Pérez, Sergio Pinilla, Anne-Florence Bitbol, Martin Weigt

Publikováno v: PLoS Computational Biology, Vol 19, Iss 3, p e1011010 (2023)

Predicting protein-protein interactions from sequences is an important goal of computational biology. Various sources of information can be used to this end. Starting from the sequences of two interacting protein families, one can use phylogeny or re

Externí odkaz: https://doaj.org/article/0065f29ea8cc4c08b6f8754f7069ec1f

Statistical physics of interacting proteins: Impact of dataset size and quality assessed in synthetic sequences

Autor: Martin Weigt, Carlos A. Gandarilla-Pérez, Anne-Florence Bitbol, Pierre Mergny

Publikováno v: Physical Review E
Physical Review E, American Physical Society (APS), 2020, 101 (3), ⟨10.1103/PhysRevE.101.032413⟩
bioRxiv
Physical Review E, 2020, 101 (3), ⟨10.1103/PhysRevE.101.032413⟩

Identifying protein-protein interactions is crucial for a systems-level understanding of the cell. Recently, algorithms based on inverse statistical physics, e.g. Direct Coupling Analysis (DCA), have allowed to use evolutionarily related sequences to

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::20049588b6057fb6f9367cc3b40b83ce
https://pubmed.ncbi.nlm.nih.gov/32290011