NLP for Chemistry – Introduction and Recent Advances

AbstractIn this half-day tutorial we will be giving an introductory overview to a number of recent applications of natural language processing to a relatively underrepresented application domain: chemistry. Specifically, we will see how neural language models (transformers) can be applied (oftentimes with near-human performance) to chemical text mining, reaction extraction, or more importantly computational chemistry (forward and backward synthesis of chemical compounds). At the same time, a number of gold standards for experimentation have been made available to the research –academic and otherwise– community. Theoretical results will be, whenever possible, supported by system demonstrations in the form of Jupyter notebooks. This tutorial targets an audience interested in bioinformatics and biomedical applications, but pre-supposes no advanced knowledge of either.