Covering: 2000 to 2025This review explores the potential of artificial intelligence (AI) in addressing challenges and accelerating molecular insights in biosynthetic pathway research, which is crucial for developing bioactive natural products with ap...
Artificial intelligence (AI) is accelerating how we conduct science, from folding proteins with AlphaFold and summarizing literature findings with large language models, to annotating genomes and prioritizing newly generated molecules for screening u...
Covering: 2016 to 2021Discovery of novel natural products has been greatly facilitated by advances in genome sequencing, genome mining and analytical techniques. As a result, the volume of data for natural products has increased over the years, which...
Covering: up to the end of 2020. The machine learning field can be defined as the study and application of algorithms that perform classification and prediction tasks through pattern recognition instead of explicitly defined rules. Among other areas,...
Covering: 2000 to 2020 Machine learning (ML) is an efficient tool for the prediction of bioactivity and the study of structure-activity relationships. Over the past decade, an emerging trend for combining these approaches with the study of natural pr...