AI comes to lead optimization: medicinal chemistry in all disease areas can be accelerated by exploiting our pre-competitive knowledge in an unbiased way.
Over the past decade, deep learning has achieved remarkable success in various artificial intelligence research areas. Evolved from the previous research on artificial neural networks, this technology has shown superior performance to other machine l...
Machine intelligence, which is normally presented as artificial intelligence, refers to the intelligence exhibited by computers. In the history of rational drug discovery, various machine intelligence approaches have been applied to guide traditional...
External content sources such as MEDLINE(®), National Institutes of Health (NIH) grants and conference websites provide access to the latest breaking biomedical information, which can inform pharmaceutical and biotechnology company pipeline decisions...
Application of computational methods in drug discovery has received increased attention in recent years as a way to accelerate drug target prediction. Based on 443 sequence-derived protein features, we applied the most commonly used machine learning ...
High-throughput compound screening is time and resource consuming, and considerable effort is invested into screening compound libraries, profiling, and selecting the most promising candidates for further testing. Active-learning methods assist the s...
During the past decade, virtual screening (VS) has evolved from traditional similarity searching, which utilizes single reference compounds, into an advanced application domain for data mining and machine-learning approaches, which require large and ...