Recent advances in deep learning for retrosynthesis
Retrosynthesis is the cornerstone of organic chemistry, providing chemists in material and
drug manufacturing access to poorly available and brand‐new molecules. Conventional rule …
drug manufacturing access to poorly available and brand‐new molecules. Conventional rule …
[HTML][HTML] A review of transformers in drug discovery and beyond
Transformer models have emerged as pivotal tools within the realm of drug discovery,
distinguished by their unique architectural features and exceptional performance in …
distinguished by their unique architectural features and exceptional performance in …
Transformer performance for chemical reactions: Analysis of different predictive and evaluation scenarios
The prediction of chemical reaction pathways has been accelerated by the development of
novel machine learning architectures based on the deep learning paradigm. In this context …
novel machine learning architectures based on the deep learning paradigm. In this context …
Chemu 2020: Natural language processing methods are effective for information extraction from chemical patents
Chemical patents represent a valuable source of information about new chemical
compounds, which is critical to the drug discovery process. Automated information extraction …
compounds, which is critical to the drug discovery process. Automated information extraction …
Towards artificial intelligence at scale in the chemical industry
Abstract In the Industry 4.0 era, the chemical industry is embracing broad adoption of
artificial intelligence (AI) and machine learning (ML) methods. This article provides a holistic …
artificial intelligence (AI) and machine learning (ML) methods. This article provides a holistic …
Recent advances in artificial intelligence for retrosynthesis
Retrosynthesis is the cornerstone of organic chemistry, providing chemists in material and
drug manufacturing access to poorly available and brand-new molecules. Conventional rule …
drug manufacturing access to poorly available and brand-new molecules. Conventional rule …
Graph convolutional networks for chemical relation extraction
Extracting information regarding novel chemicals and chemical reactions from chemical
patents plays a vital role in the chemical and pharmaceutical industry. Due to the increasing …
patents plays a vital role in the chemical and pharmaceutical industry. Due to the increasing …
Ensemble of deep masked language models for effective named entity recognition in health and life science corpora
The health and life science domains are well known for their wealth of named entities found
in large free text corpora, such as scientific literature and electronic health records. To …
in large free text corpora, such as scientific literature and electronic health records. To …
A Dataset for Evaluating Contextualized Representation of Biomedical Concepts in Language Models
Due to the complexity of the biomedical domain, the ability to capture semantically
meaningful representations of terms in context is a long-standing challenge. Despite …
meaningful representations of terms in context is a long-standing challenge. Despite …
Correction to automated chemical reaction extraction from scientific literature
We missed a relevant reference to the ChEMU (Cheminformatics Elsevier Melbourne
University) evaluation lab held in 2020, 1− 4 which shared similar missions with our work …
University) evaluation lab held in 2020, 1− 4 which shared similar missions with our work …