Editorial: Machine learning, epistasis, and protein engineering: From sequence-structure-function relationships to regulation of metabolic pathways

Frederic Cadet (1, 2, 3) , Emma Saavedra (4) , Per-Olof Syren (5) , Brigitte Gontero (6)

1 DSIMB Réunion - Dynamique des Structures et Interactions des Macromolécules Biologiques - Pôle de La Réunion
2 Labex Gr-Ex - Laboratoire d'Excellence : Biogenèse et pathologies du globule rouge
3 PEACCEL - Protein Engineering Accelerator [Paris]
4 Instituto Nacional de Cardiologia Ignacio Chavez
5 KTH - KTH Royal Institute of Technology [Stockholm]
6 BIP - Bioénergétique et Ingénierie des Protéines

Mots clés: epistasis; non-linear interactions; machine learning; artificial intelligence; RNA enzyme; Crohn 's disease; antibiotic resistance; Protein-protein interaction networks

Domaines: Sciences du Vivant [q-bio]

Frederic Cadet, Emma Saavedra, Per-Olof Syren, Brigitte Gontero. Editorial: Machine learning, epistasis, and protein engineering: From sequence-structure-function relationships to regulation of metabolic pathways. Frontiers in Molecular Biosciences, 2022, ⟨10.3389/fmolb.2022.1098289⟩. ⟨hal-03881943⟩