Scientists at the University of California, Irvine have developed a new deep-learning framework that predicts gene regulation at the single-cell level.
Biotechnology
Jan 06, 2021
0
194
A joint research team from KAIST and UCSD has developed a deep neural network named DeepTFactor that predicts transcription factors from protein sequences. DeepTFactor will serve as a useful tool for understanding the regulatory ...
Molecular & Computational biology
Jan 05, 2021
0
13
A team of scientists at Freie Universität Berlin has developed an artificial intelligence (AI) method for calculating the ground state of the Schrödinger equation in quantum chemistry. The goal of quantum chemistry is to ...
Quantum Physics
Dec 21, 2020
0
19486
Whether at a birthday party in Brazil, a funeral in Kenya or protests in Hong Kong, humans all use variations of the same facial expressions in similar social contexts, such as smiles, frowns, grimaces and scowls, a new study ...
Social Sciences
Dec 16, 2020
2
148
The role of deep learning in science is at a turning point, with weather, climate, and Earth systems modeling emerging as an exciting application area for physics-informed deep learning that can more effectively identify ...
Earth Sciences
Sep 04, 2020
0
10
Computer systems that emulate key aspects of human problem solving are commonly referred to as artificial intelligence (AI). This field has seen massive progress over the last years. Most notably, deep learning enabled groundbreaking ...
Biotechnology
Aug 04, 2020
0
31
A naturally occurring injection of underground fluids drove a four-year-long earthquake swarm near Cahuilla, California, according to a new seismological study that utilizes advances in earthquake monitoring with a machine-learning ...
Earth Sciences
Jun 18, 2020
4
357
Scientists are using algorithms and machine learning to listen for the distinct calls of one of the world's most endangered animals in a bid to identify where they are and shield them from one of their greatest threats.
Plants & Animals
Apr 29, 2020
0
3
An Australian-German collaboration has demonstrated fully-autonomous SPM operation, applying artificial intelligence and deep learning to remove the need for constant human supervision.
General Physics
Mar 26, 2020
1
228
An artifact-free computational approach to extract the phase of light from noisy intensity signals improves imaging of transparent objects, such as biological cells, under low light conditions. The procedure separates intensity ...
Optics & Photonics
Mar 20, 2020
0
10
