Cargando…
Artificial Intelligence in Drug Discovery: A Comprehensive Review of Data-driven and Machine Learning Approaches
As expenditure on drug development increases exponentially, the overall drug discovery process requires a sustainable revolution. Since artificial intelligence (AI) is leading the fourth industrial revolution, AI can be considered as a viable solution for unstable drug research and development. Gene...
Autores principales: | Kim, Hyunho, Kim, Eunyoung, Lee, Ingoo, Bae, Bongsung, Park, Minsu, Nam, Hojung |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
The Korean Society for Biotechnology and Bioengineering
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7790479/ https://www.ncbi.nlm.nih.gov/pubmed/33437151 http://dx.doi.org/10.1007/s12257-020-0049-y |
Ejemplares similares
-
DeepConv-DTI: Prediction of drug-target interactions via deep learning with convolution on protein sequences
por: Lee, Ingoo, et al.
Publicado: (2019) -
Artificial Intelligence and Machine Learning Technology Driven Modern Drug Discovery and Development
por: Sarkar, Chayna, et al.
Publicado: (2023) -
LOGICS: Learning optimal generative distribution for designing de novo chemical structures
por: Bae, Bongsung, et al.
Publicado: (2023) -
Sequence-based prediction of protein binding regions and drug–target interactions
por: Lee, Ingoo, et al.
Publicado: (2022) -
Drug repositioning of herbal compounds via a machine-learning approach
por: Kim, Eunyoung, et al.
Publicado: (2019)