AIMC Topic: Chemistry Techniques, Synthetic

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RetroComposer: Composing Templates for Template-Based Retrosynthesis Prediction.

Biomolecules Sep 19, 2022
The main target of retrosynthesis is to recursively decompose desired molecules into available building blocks. Existing template-based retrosynthesis methods follow a template selection stereotype and suffer from limited training templates, which pr...
Machine Learning Models, Chemical Chemistry Techniques, Synthetic
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Unified Deep Learning Model for Multitask Reaction Predictions with Explanation.

Journal of chemical information and modeling Mar 10, 2022
There is significant interest and importance to develop robust machine learning models to assist organic chemistry synthesis. Typically, task-specific machine learning models for distinct reaction prediction tasks have been developed. In this work, w...
Machine Learning Deep Learning Natural Language Processing Chemistry Techniques, Synthetic
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Materials Precursor Score: Modeling Chemists' Intuition for the Synthetic Accessibility of Porous Organic Cage Precursors.

Journal of chemical information and modeling Aug 13, 2021
Computation is increasingly being used to try to accelerate the discovery of new materials. One specific example of this is porous molecular materials, specifically porous organic cages, where the porosity of the materials predominantly comes from th...
Intuition Porosity Machine Learning Chemistry Techniques, Synthetic
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Toward autonomous design and synthesis of novel inorganic materials.

Materials horizons May 26, 2021
Autonomous experimentation driven by artificial intelligence (AI) provides an exciting opportunity to revolutionize inorganic materials discovery and development. Herein, we review recent progress in the design of self-driving laboratories, including...
Algorithms Robotics Chemistry Techniques, Synthetic Automation Artificial Intelligence
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Artificial intelligence to deep learning: machine intelligence approach for drug discovery.

Molecular diversity Apr 12, 2021
Drug designing and development is an important area of research for pharmaceutical companies and chemical scientists. However, low efficacy, off-target delivery, time consumption, and high cost impose a hurdle and challenges that impact drug design a...
Drug Design Drug Discovery Research Design Animals Drug Development Support Vector Machine Models, Molecular Deep Learning Big Data Humans Machine Learning Algorithms Artificial Intelligence Chemistry Techniques, Synthetic Data Mining Quantitative Structure-Activity Relationship
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Computational planning of the synthesis of complex natural products.

Nature Oct 13, 2020
Training algorithms to computationally plan multistep organic syntheses has been a challenge for more than 50 years. However, the field has progressed greatly since the development of early programs such as LHASA, for which reaction choices at each s...
Benzylisoquinolines Indole Alkaloids Chemistry, Organic Chemistry Techniques, Synthetic Tetrahydroisoquinolines Lactones Sesquiterpenes Macrolides Indans Automation Reproducibility of Results Biological Products Knowledge Bases Artificial Intelligence Software
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Transfer learning enables the molecular transformer to predict regio- and stereoselective reactions on carbohydrates.

Nature communications Sep 25, 2020
Organic synthesis methodology enables the synthesis of complex molecules and materials used in all fields of science and technology and represents a vast body of accumulated knowledge optimally suited for deep learning. While most organic reactions i...
Molecular Structure Carbohydrates Chemistry Techniques, Synthetic Carbohydrate Metabolism Machine Learning Oligosaccharides Glycosylation
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Transfer Learning: Making Retrosynthetic Predictions Based on a Small Chemical Reaction Dataset Scale to a New Level.

Molecules (Basel, Switzerland) May 19, 2020
Effective computational prediction of complex or novel molecule syntheses can greatly help organic and medicinal chemistry. Retrosynthetic analysis is a method employed by chemists to predict synthetic routes to target compounds. The target compounds...
Datasets as Topic Chemistry, Pharmaceutical Machine Learning Algorithms Chemistry Techniques, Synthetic Computational Chemistry Humans Artificial Intelligence
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"Ring Breaker": Neural Network Driven Synthesis Prediction of the Ring System Chemical Space.

Journal of medicinal chemistry May 13, 2020
Ring systems in pharmaceuticals, agrochemicals, and dyes are ubiquitous chemical motifs. While the synthesis of common ring systems is well described and novel ring systems can be readily and computationally enumerated, the synthetic accessibility of...
Chemistry Techniques, Synthetic Hydrocarbons, Cyclic Neural Networks, Computer Databases, Chemical Heterocyclic Compounds
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Current and Future Roles of Artificial Intelligence in Medicinal Chemistry Synthesis.

Journal of medicinal chemistry Apr 14, 2020
Artificial intelligence and machine learning have demonstrated their potential role in predictive chemistry and synthetic planning of small molecules; there are at least a few reports of companies employing synthetic planning into their overall appr...
Chemistry Techniques, Synthetic Models, Chemical Chemical Industry Chemistry, Pharmaceutical Machine Learning Pharmaceutical Research Drug Discovery
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