By CASP13, in 2018, most groups were using deep learning to predict protein structures, pushing accuracy levels up to about 60%. Top marks that year went to AlphaFold, a model designed by researchers ...

Abstract: This manuscript focuses on the application of deep recurrent learning techniques to build rational behaviour of an autonomous agent. The purpose of this study is to compare the ...

Artificial Intelligence (AI) is rapidly taking over industries. The fear of job displacements is palpable; however, as companies around the world are scrambling to automate various processes, ...

The Nature Index 2025 Research Leaders — previously known as Annual Tables — reveal the leading institutions and countries/territories in the natural and health sciences, according to their output in ...

The Nature Index 2025 Research Leaders — previously known as Annual Tables — reveal the leading institutions and countries/territories in the natural and health sciences, according to their output in ...

Introducing Annotatability—a powerful new framework to address a major challenge in biological research by examining how artificial neural networks learn to label genomic data. Genomic datasets often ...

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. Attention-based decoder models were used to generate libraries of novel inhibitors for ...

The model, the training history, and its application to the test set are contained into the noteook. Its aim is just demonstrative. In particular the architecture and the loss function used for the ...

The study is part of the PsychENCODE Consortium, which brings together multidisciplinary teams to generate large-scale gene expression and regulatory data from human brains across several major ...

Through the looking glass: If this week's science news is anything to go by, it won't be long before Big Brother is peering inside our heads. Coming on the heels of US scientists revealing a GPT model ...