SPaDe-CSP first predicts most probable space groups and crystal densities using machine learning and then employs an efficient neural network potential for structure refinement. Prediction of crystal ...

Researchers from the Massachusetts Institute of Technology (MIT) Jameel Clinic for Machine Learning in Health have announced the open-source release of Boltz-2, which now predicts molecular binding ...

Researchers have devised a mathematical approach to predict the structures of crystals -- a critical step in developing many medicines and electronic devices -- in a matter of hours using only a ...

In what ways does chromatographic co-elution affect MS2 spectral quality, molecular networking, and the accuracy of ML models trained on MS2 data?

However, crystal structure prediction (CSP) is an inherently challenging task due to the weak and diverse intra- and intermolecular interactions unique to organic crystals. Even minor variations can ...

Soil liquefaction—the process where saturated soil loses its structure and transforms to a fluid-like state—can have devastating outcomes, as evidenced by the Great East Japan Earthquake in 2011.

AI protein function prediction uses machine learning models trained on sequence and structural data to infer protein roles at ...