It is widely known that the traditional drug discovery and development process is extremely time-consuming, expensive and challenging; taking an […]
Due to the complex nature of central nervous system diseases and the presence of the blood-brain barrier (among other factors), […]
A recent study, published in Scientific Reports, designed a test system using machine learning to systematically examine the structural features […]
At the time of writing, there have been 137 million cases and nearly 3 million deaths from COVID-19. Although some targets […]
Epigenetic targets are of significant importance in drug discovery research, and there is increasing availability of chemogenomic data related to […]
Researchers at Queen Mary University of London have developed a machine learning algorithm – DRUML – that ranks drugs based […]
We summarise a recent study, published as preprint in medrxiv, that explored the hypothesis that a data-driven analysis of a […]
Researchers have developed a machine-learning (ML) framework to identify robust drug biomarkers and thereby, predict anti-cancer drug efficacy. Biomarker identification […]
A team of researchers have developed a machine learning (ML)-based algorithm to analyse electronic health record (EHR) data and reliably […]
Here, we summarise a chapter in Artificial Intelligence in Oncology Drug Discovery and Development, which explored the role of electronic […]
