LJI scientists develop new method to match genes to their molecular ‘switches’

LA JOLLA, CA—Scientists at La Jolla Institute for Immunology (LJI) have developed a new computational method for linking molecular marks on our DNA to gene activity. Their work may help researchers connect genes to the molecular “switches” that turn them on or off. This research, published in Genome Biology, is an important step toward harnessing machine learning approaches to better understand links between gene expression and disease development.

New neural network uses common sense to make fake bird images from text

In an effort to generate high-quality images based on text descriptions, a group of researchers in China built a generative adversarial network that incorporates data representing common-sense knowledge. Their method uses common sense to clarify the starting point for image generation and also uses common sense to enhance different specific features of the generated image at three different levels of resolution.

Study shows how machine learning could predict rare disastrous events, like earthquakes or pandemics

When it comes to predicting disasters brought on by extreme events (think earthquakes, pandemics or “rogue waves” that could destroy coastal structures), computational modeling faces an almost insurmountable challenge: Statistically speaking, these events are so rare that there’s just not enough data on them to use predictive models to accurately forecast when they’ll happen next.

Supercomputers Help Advance Computational Chemistry

Researchers at the Massachusetts Institute of Technology (MIT) have succeeded in developing an artificial intelligence (AI) approach to detect electron correlation – the interaction between a system’s electrons – which is vital but expensive to calculate in quantum chemistry.