BERT Learns (and Teaches) Chemistry
#BERT #Machine Learning #Drug Discovery #Organic Chemistry #Attention Mechanism #Molecular Synthesis #arXiv
📌 Key Takeaways
- Researchers successfully applied the BERT transformer model to the field of computational organic chemistry.
- The study focuses on using 'attention' mechanisms to analyze functional groups and molecular properties.
- The model aims to solve major problems including drug discovery and product prediction.
- This data-driven approach treats molecular structures like a language to improve synthesis workflows.
📖 Full Retelling
🏷️ Themes
Machine Learning, Organic Chemistry, Artificial Intelligence
📚 Related People & Topics
Machine learning
Study of algorithms that improve automatically through experience
Machine learning (ML) is a field of study in artificial intelligence concerned with the development and study of statistical algorithms that can learn from data and generalize to unseen data, and thus perform tasks without explicit instructions. Within a subdiscipline in machine learning, advances i...
Organic chemistry
Subdiscipline of chemistry, focusing on carbon compounds
Organic chemistry is a subdiscipline within chemistry involving the scientific study of the structure, properties, and reactions of organic compounds and organic materials, i.e., matter in its various forms that contain carbon atoms. Study of structure determines their structural formula. Study of p...
Drug discovery
Pharmaceutical procedure
In the fields of medicine, biotechnology, and pharmacology, drug discovery is the process by which new candidate medications are discovered. Historically, drugs were discovered by identifying the active ingredient from traditional remedies or by serendipitous discovery, as with penicillin. More rece...
🔗 Entity Intersection Graph
Connections for Machine learning:
- 🌐 Large language model (7 shared articles)
- 🌐 Generative artificial intelligence (3 shared articles)
- 🌐 Electroencephalography (3 shared articles)
- 🌐 Natural language processing (2 shared articles)
- 🌐 Artificial intelligence (2 shared articles)
- 🌐 Graph neural network (2 shared articles)
- 🌐 Neural network (2 shared articles)
- 🌐 Computer vision (2 shared articles)
- 🌐 Transformer (1 shared articles)
- 🌐 User interface (1 shared articles)
- 👤 Stuart Russell (1 shared articles)
- 🌐 Ethics of artificial intelligence (1 shared articles)
📄 Original Source Content
arXiv:2007.16012v1 Announce Type: cross Abstract: Modern computational organic chemistry is becoming increasingly data-driven. There remain a large number of important unsolved problems in this area such as product prediction given reactants, drug discovery, and metric-optimized molecule synthesis, but efforts to solve these problems using machine learning have also increased in recent years. In this work, we propose the use of attention to study functional groups and other property-impacting m