Machine learning enhances proteomics by optimizing peptide identification, structure prediction, and biomarker discovery.

After uncovering a unifying algorithm that links more than 20 common machine-learning approaches, researchers organized them into a 'periodic table of machine learning' that can help scientists ...

When experiments are impractical, density functional theory (DFT) calculations can give researchers accurate approximations of chemical properties. The mathematical equations that underpin the ...

Researchers have created a unifying framework that can help scientists combine existing ideas to improve AI models or create new ones. (Nanowerk News) MIT researchers have created a periodic table ...

MIT researchers created a periodic table of machine learning that shows how more than 20 classical algorithms are connected. The new framework sheds light on how scientists could fuse strategies from ...

MIT researchers have created a periodic table that shows how more than 20 classical machine-learning algorithms are connected. The new framework sheds light on how scientists could fuse strategies ...

Accuracy and speedup achieved with the Weighted Active Space Protocol (WASP) for methane activation on titanium carbide. (Figure courtesy of Seal et al.) Catalysts play an indispensable role in modern ...

In a recent study published in Scientific Reports, researchers developed a machine learning-based heart disease prediction model (ML-HDPM) that uses various combinations of information and numerous ...

Correctly distinguishing between related neurodegenerative diseases remains challenging for clinicians, because reliable markers do not yet exist for many disorders. In the July 22 Neurology, ...