AI tagged posts

Researchers from the University of Bonn have trained an AI process to predict potential active ingredients with special properties. Therefore, they derived a chemical language model — a kind of ChatGPT for molecules. Following a training phase, the AI was able to exactly reproduce the chemical structures of compounds with known dual-target activity that may be particularly effective medications...

An estimated one in five Americans live with chronic pain and current treatment options leave much to be desired. Feixiong Cheng, Ph.D., Director of Cleveland Clinic’s Genome Center, and IBM are using artificial intelligence (AI) for drug discovery in advanced pain management. The team’s deep-learning framework identified multiple gut microbiome-derived metabolites and FDA-approved drugs that can be repurposed to select non-addictive, non-opioid options to treat chronic pain.

The findings, published in Cell Press, represent one of many ways the organizations’ Discovery Accelerator partnership is helping to advance research in healthcare and life sciences.

Treating chronic pain with opioids is still a challenge due to the risk of severe side eff...

An AI-powered tool can distinguish dark matter’s elusive effects from other cosmic phenomena, which could bring us closer to unlocking the secrets of dark matter.

Dark matter is the invisible force holding the universe together – or so we think. It makes up around 85% of all matter and around 27% of the universe’s contents, but since we can’t see it directly, we have to study its gravitational effects on galaxies and other cosmic structures. Despite decades of research, the true nature of dark matter remains one of science’s most elusive questions.

According to a leading theory, dark matter might be a type of particle that barely interacts with anything else, except through gravity...

Researchers from LMU, the ORIGINS Excellence Cluster, the Max Planck Institute for Extraterrestrial Physics (MPE), and the ORIGINS Data Science Lab (ODSL) have made an important breakthrough in the analysis of exoplanet atmospheres.

Using physics-informed neural networks (PINNs), they have managed to model the complex light scattering in the atmospheres of exoplanets with greater precision than has previously been possible.

This method opens up new opportunities for the analysis of exoplanet atmospheres, especially with regard to the influence of clouds, and could significantly improv...