Deep in the dense coastal forests and marshes of the American Southeast lie shell rings and shell mounds left by Indigenous people 3,000 to 5,000 years ago. Now an international team of researchers, using deep machine learning ...
We all have an internal clock but what makes us tick? Scientists at the Earlham Institute and IBM Research have developed new artificial intelligence (AI) and machine learning (ML) technology to understand how gene expression ...
A team of scientists at the University of Illinois Chicago has developed a software tool that can help researchers more efficiently identify the regulators of genes. The system leverages a machine learning algorithm to predict ...
The Structural Bioinformatics and Network Biology laboratory, led by ICREA Researcher Dr. Patrick Aloy, has completed the bioactivity information for a million molecules using deep machine-learning computational models. It ...
While crop yield has achieved a substantial boost from nanotechnology in recent years, alarms over the health risks posed by nanoparticles within fresh produce and grains have also increased. In particular, nanoparticles ...
Researchers from Carnegie Mellon University's Computational Biology Department in the School of Computer Science have developed a new process that could reinvigorate the search for natural product drugs to treat cancers, ...
Researchers from Tokyo Metropolitan University have enhanced "super-resolution" machine learning techniques to study phase transitions. They identified key features of how large arrays of interacting particles behave at different ...
The field of mathematical topology is often described in terms of donuts and pretzels.
A new theorem from the field of quantum machine learning has poked a major hole in the accepted understanding about information scrambling.
Argonne scientists across several disciplines have combined forces to create a new process for testing and predicting the effects of high temperatures on refractory oxides.
