Cambridge researchers map the convergence of biomarkers, digital phenotyping, and AI toward biologically grounded ...

The field of oncology is currently undergoing a transformation driven by high-throughput proteomics, genomics, and advanced single-cell technologies. These ...

Drug discovery is like molecular Tetris. Chemists snap atoms together, adjusting the pieces until everything fits and suddenly, a molecule makes a promising new medicine.

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

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 ...

Researchers developed a machine-learning workflow that predicts how chemical reactions will form specific “handed” versions of molecules—critical for safe and effective drugs. Trained on small ...

Cancer immunotherapies often rely on activating immune responses, yet many tumors remain resistant because their internal survival mechanisms are poorly understood.

Natural systems like green fluorescent protein (GFP) exploit nanoconfinement to stabilize molecules within protective cavities. Mimicking this bioinspired strategy, we engineer DNA frameworks that ...

Abstract: A Deep Learning-based Framework of Molecular Structure Analysis of Drugs discovery is an article that provides an opportunity to improve the quality and accuracy of prediction of molecular ...

Abstract: Accurately predicting molecular properties can identify more promising drug candidates and facilitate the process of drug discovery. There are advances in methods for molecular property ...