Bacteria can still develop antibiotic resistance even in the face of challenging genetic tradeoffs, or compromises, associated with varying antibiotic concentrations, says a new study published today in eLife.
The Chemical Checker provides processed, harmonized and ready-to-use bioactivity information on more than 1M small molecules. The tool, developed by the Structural Bioinformatics and Network Biology lab at IRB Barcelona, has been published in Nature Biotechnology.
As the virus causing COVID-19 began its devastating spread, an international team of scientists was alarmed by the lack of uniform approaches by various countries' epidemiologists. Data modeling to predict the numbers of likely infections varied widely. In the journal Chaos, the group describes why modeling and extrapolating the evolution of COVID-19 outbreaks in near real time is an enormous scientific challenge that requires a deep understanding of the nonlinearities underlying the dynamics of epidemics.
Rice engineers have found a way to train deep neural networks for a fraction of the energy required today. Their Early Bird method finds key network connectivity patterns early in training, reducing the computations and carbon footprint for training deep learning.
New study finds the national rate of death among people infected with the novel coronavirus -- SARS-CoV-2 -- that causes COVID-19 and who show symptoms is 1.3%, the study found. The comparable rate of death for the seasonal flu is 0.1%.
Algorithms and deep learning has enabled Flinders University sleep researchers to dive deep into one of the mysteries of sleep health. They have used machine learning and artificial intelligence to develop a free online tool being used by sleep experts and researchers around the world to work out the role of the so-called K-complex, a prominent, brief up-down-up pattern of brain electro-encephalogram (EEG) electrical activity lasting around half a second during sleep.
An interdisciplinary team of Kansas State University researchers developed a computer simulation that revealed beef supply chain vulnerabilities that need safeguarding -- a realistic concern during the COVID-19 pandemic.
Since the beginning of March, public life in Germany has been severely restricted due to the corona pandemic. Following the encouraging decline in the number of new cases of COVID-19, the debate on the effectiveness of interventions taken to date and on further relaxation of the restrictions is meanwhile gaining momentum.
Robots can be made from soft materials, but the flexibility of such robots is limited by the inclusion of rigid sensors necessary for their control. Researchers created embedded sensors, to replace rigid sensors, that offer the same functionality but afford the robot greater flexibility. Soft robots can be more adaptable and resilient than more traditional rigid designs. The team used cutting-edge machine learning techniques to create their design.
A team of researchers co-led by Berkeley Lab has observed unusually long-lived wavelike electrons called 'plasmons' in a new class of electronically conducting material. Plasmons are very important for determining the optical and electronic properties of metals for the development of new sensors and communication devices.