Drug discovery is like molecular Tetris. Chemists snap atoms together, adjusting the pieces until everything fits, and ...

As geopolitical instability reshapes global trade routes and energy markets, molecular-level verification is emerging ...

The large language model automates literature search, synthesis, and structural analysis to speed up materials discovery and ...

Researchers have developed a human intestinal cell model that closely mimics the structure and function of the human gut, enabling more precise prediction of drug-induced gastrointestinal toxicity ...

Innate immune sensors—known as pattern recognition receptors (PRRs)—detect specific molecular components of bacterial or ...

A leading oncologist proposes classifying metastatic cancer by molecular alterations rather than organ origin, arguing that the shift could accelerate drug access.

What if the thermal noise that hinders the efficiency of both classical and quantum computers could, instead, be used as a ...

Abstract: Predicting molecular properties is vital for drug discovery, but experimental measurement is costly and limited by scarce labeled data. Self-supervised molecular pretraining can leverage ...

Recursive language models (RLMs) are an inference technique developed by researchers at MIT CSAIL that treat long prompts as an external environment to the model. Instead of forcing the entire prompt ...

Given the ubiquitous presence of water during catalyst synthesis, storage, and application, interactions between water and molecular sieves, along with their consequent effects on frameworks and ...