Results 1 to 10 of about 92 (69)
Science and Technology of Advanced Materials, 2022 Recently, artificial intelligence (AI)-enabled de novo molecular generators (DNMGs) have automated molecular design based on data-driven or simulation-based property estimates.
Takehiro Fujita +6 more
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Low-Data Drug Design with Few-Shot Generative Domain Adaptation
Bioengineering, 2023 Developing new drugs for emerging diseases, such as COVID-19, is crucial for promoting public health. In recent years, the application of artificial intelligence (AI) has significantly advanced drug discovery pipelines.
Ke Liu +3 more
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Employment of electric torch discharge and a steam-gas generator in surface schooping of materials [PDF]
Радиофизика и электроника, 2020 Subject and Purpose. The present paper is concerned with the method of surface schooping of materials using high-frequency torch discharge (HFTD) and glycerol vapor as a base for dissolving activating additives to the working gas. To approach the problem,
A.O. Puzanov
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Journal of Cheminformatics, 2023 Computational molecular design can yield chemically unreasonable compounds when performed carelessly. A popular strategy to mitigate this risk is mimicking reference chemistry.
Alan Kerstjens, Hans De Winter
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Scientific Reports, 2023 The discovery of potential therapeutic agents for life-threatening diseases has become a significant problem. There is a requirement for fast and accurate methods to identify drug-like molecules that can be used as potential candidates for novel targets.
Karthik Viswanathan +4 more
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Improving de novo Molecule Generation by Embedding LSTM and Attention Mechanism in CycleGAN
Frontiers in Genetics, 2021 The application of deep learning in the field of drug discovery brings the development and expansion of molecular generative models along with new challenges in this field.
Feng Wang +6 more
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Molecular generation by Fast Assembly of (Deep)SMILES fragments
Journal of Cheminformatics, 2021 Background In recent years, in silico molecular design is regaining interest. To generate on a computer molecules with optimized properties, scoring functions can be coupled with a molecular generator to design novel molecules with a desired property ...
Francois Berenger, Koji Tsuda
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COMA: efficient structure-constrained molecular generation using contractive and margin losses
Journal of Cheminformatics, 2023 Background Structure-constrained molecular generation is a promising approach to drug discovery. The goal of structure-constrained molecular generation is to produce a novel molecule that is similar to a given source molecule (e.g. hit molecules) but has
Jonghwan Choi +2 more
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MORTAR: a rich client application for in silico molecule fragmentation
Journal of Cheminformatics, 2023 Developing and implementing computational algorithms for the extraction of specific substructures from molecular graphs (in silico molecule fragmentation) is an iterative process.
Felix Bänsch +6 more
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Journal of Cheminformatics, 2012 Computer Assisted Structure Elucidation has been used for decades to discover the chemical structure of unknown compounds. In this work we introduce the first open source structure generator, Open Molecule Generator (OMG), which for a given elemental ...
Peironcely Julio E +6 more
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