A team of researchers have developed a semi-supervised machine learning approach to define antimalarial drug action from heterogenous cell-based screens. […]
A recent article proposed the mining of knowledge graphs to identify biomolecular adverse drug reaction mechanisms, which at present largely […]
A recent study developed, validated and evaluated drug-drug interaction algorithms that alert clinicians to potentially harmful interactions, which take advantage […]
A recent study presented a novel computational method for inferring drug-target interactions, which exploits the primary protein sequence and molecular […]
A recent study, published in Drug Safety, aimed to describe the adverse drug reactions reported in inflammatory bowel disease patients […]
Predicting novel drug-target interactions plays an important role in identifying new drug candidates and finding new proteins to target. An […]
A recent article, published in Communications Biology, has outlined a method for expanding our understanding of host-microbiome interactions that will […]
Researchers from the Laboratory of Computational Systems Biotechnology at EPFL, Switzerland, have developed a database – NICEdrug.ch – that could […]
For the first time, a review explored in depth how big data and artificial intelligence (AI) techniques are currently being […]
Researchers have developed a machine learning algorithm, called NRPminer, that makes it easier for scientists to develop drugs from natural […]
