Cargando…
Multiobjective de novo drug design with recurrent neural networks and nondominated sorting
Research productivity in the pharmaceutical industry has declined significantly in recent decades, with higher costs, longer timelines, and lower success rates of drug candidates in clinical trials. This has prioritized the scalability and multiobjectivity of drug discovery and design. De novo drug...
Autor principal: | Yasonik, Jacob |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer International Publishing
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7026957/ https://www.ncbi.nlm.nih.gov/pubmed/33430996 http://dx.doi.org/10.1186/s13321-020-00419-6 |
Ejemplares similares
-
A Bee Evolutionary Guiding Nondominated Sorting Genetic Algorithm II for Multiobjective Flexible Job-Shop Scheduling
por: Deng, Qianwang, et al.
Publicado: (2017) -
Memory augmented recurrent neural networks for de-novo drug design
por: Suresh, Naveen, et al.
Publicado: (2022) -
Applications of Nondominated Sorting Genetic Algorithm II Combined with WKNN Online Matching Algorithm in Building Indoor Optimization Design
por: Yu, Xiwen, et al.
Publicado: (2022) -
Multiobjective heuristic algorithm for de novo protein design in a quantified continuous sequence space
por: Li, Rui-Xiang, et al.
Publicado: (2021) -
De novo drug design by iterative multiobjective deep reinforcement learning with graph-based molecular quality assessment
por: Fang, Yi, et al.
Publicado: (2023)