Cargando…
Understanding the evolution of a de novo molecule generator via characteristic functional group monitoring
Recently, artificial intelligence (AI)-enabled de novo molecular generators (DNMGs) have automated molecular design based on data-driven or simulation-based property estimates. In some domains like the game of Go where AI surpassed human intelligence, humans are trying to learn from AI about the bes...
Autores principales: | Fujita, Takehiro, Terayama, Kei, Sumita, Masato, Tamura, Ryo, Nakamura, Yasuyuki, Naito, Masanobu, Tsuda, Koji |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Taylor & Francis
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9176351/ https://www.ncbi.nlm.nih.gov/pubmed/35693890 http://dx.doi.org/10.1080/14686996.2022.2075240 |
Ejemplares similares
-
De novo creation of a naked eye–detectable fluorescent molecule based on quantum chemical computation and machine learning
por: Sumita, Masato, et al.
Publicado: (2022) -
Deep-learning-based inverse design of three-dimensional architected cellular materials with the target porosity and stiffness using voxelized Voronoi lattices
por: Zheng, Xiaoyang, et al.
Publicado: (2023) -
NMR-TS: de novo molecule identification from NMR spectra
por: Zhang, Jinzhe, et al.
Publicado: (2020) -
QCforever: A Quantum
Chemistry Wrapper for Everyone
to Use in Black-Box Optimization
por: Sumita, Masato, et al.
Publicado: (2022) -
Accelerated discovery of high-performance Al-Si-Mg-Sc casting alloys by integrating active learning with high-throughput CALPHAD calculations
por: Gao, Jianbao, et al.
Publicado: (2023)