In the last two decades, mass digitization has dramatically changed the landscape of scholarly research. The ability to ...

SeamlessTx is addressing this challenge with a unique platform that integrates large-scale directed evolution and machine learning (ML)-driven models to predict recombinase variant activity and ...

Artificial intelligence is advancing at a dizzying speed. Like many new technologies, it offers significant benefits but also ...

Early-warning signs of marsh decline provided by the model could be crucial for conservation. “Once [marsh] loss occurs, that ...

Researchers from MIT, Microsoft, and Google have introduced a “periodic table of machine learning” that stands to unify many different machine learning techniques using a single framework. Their ...

From the smallest fragment of brain tissue, the intricate blueprint of the entire brain is beginning to emerge. Researchers at Baylor College of Medicine are making several time-consuming aspects of ...

Optimization of machine learning decoders to classify sequence-embedded finger movements from MEG activity reached approximately 94% accuracy. The representation manifolds of the same action performed ...

Machine learning approaches for predicting protein-ligand binding sites from sequence data Orhun Vural * Leon Jololian Department of Electrical and Computer Engineering, The University of Alabama at ...

Think about a toolbox for a moment. You have different tools for different jobs. A screwdriver makes a poor hammer, for ...