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Scientists have used several machine learning models to predict bacterial gene exchange, which could reveal novel antibiotic targets.
A new computer-aided tool maps allosteric sites in G protein-coupled receptors to search for allosteric drugs to treat a range of diseases.
Scientists have identified potential cancer drugs to treat pulmonary hypertension using experimental and computational approaches.
Researchers have visualised SARS-CoV-2 protein dynamics using in silico methods. In this article, Navodya Roemer explains how a team from the University of Warwick developed a computational strategy that could assist scientists in the production of new treatments and drugs for COVID-19.
An MIT study has used the first statistical model to finely characterise how ketamine anaesthesia affects the brain, possibly improving patient outcomes.
View Drug Target Review's new infographic on the use of AI and informatics within early therapeutic development here.
Laboratories operating under GMP or GLP regulations must follow guidelines set by agencies to protect scientific integrity or demonstrate quality assurance of manufactured products.
Artificial intelligence was shown to predict the 3D shapes of RNA molecules, which could significantly advance RNA therapeutics.
An artificial intelligence technique can identify which neoantigens are recognised by the immune system, possibly improving cancer prognosis and treatment.
Sheraz Gul explores how machine learning and artificial intelligence represent an exciting opportunity for the drug discovery industry, with the potential to develop highly optimised small molecules.
Learn how you can partner for success with Eurofins Beacon Discovery’s industry leading GPCR experts to support your program from concept to clinic.
Researchers have created a tool that allows glycomics datasets to be analysed using artificial intelligence for early cancer diagnoses.
The new study modelled the process of capsid disassembly of the hepatitis B virus at an atomic level to help develop targeted therapies.
Researchers have developed a novel algorithm, “scArches”, that can compare data on single-cell genomics to better understand diseases.