Cargando…
Deep generative models for peptide design
Computers can already be programmed for superhuman pattern recognition of images and text. For machines to discover novel molecules, they must first be trained to sort through the many characteristics of molecules and determine which properties should be retained, suppressed, or enhanced to optimize...
Autores principales: | Wan, Fangping, Kontogiorgos-Heintz, Daphne, de la Fuente-Nunez, Cesar |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
RSC
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9189861/ https://www.ncbi.nlm.nih.gov/pubmed/35769205 http://dx.doi.org/10.1039/d1dd00024a |
Ejemplares similares
-
Editorial: Antimicrobial Peptides: Molecular Design, Structure-Function Relationship, and Biosynthesis Optimization
por: Hao, Ya, et al.
Publicado: (2022) -
Deep generative design with 3D pharmacophoric constraints
por: Imrie, Fergus, et al.
Publicado: (2021) -
Deep Eutectic Solvents as Media for the Prebiotic DNA-Templated Synthesis of Peptides
por: Núñez-Pertíñez, Samuel, et al.
Publicado: (2020) -
Structure-based de novo drug design using 3D deep generative models
por: Li, Yibo, et al.
Publicado: (2021) -
Editorial: Community series in antimicrobial peptides: Molecular design, structure function relationship and biosynthesis optimization
por: Yang, Na, et al.
Publicado: (2023)