Machine learning enables long-awaited code breakthrough with potential applications in biomedicine. Scientists have long known that human genes spring into action through instructions delivered by the precise order of our DNA, directed by the four different types of individual links, or “bases,” coded A, C, G and T.

Nearly 25% of our genes are widely known to be transcribed by sequences that resemble TATAAA, which is called the “TATA box...

Using a new algorithm, researchers have reconstructed the movements of individual particles of light to see through clouds, fog and other obstructions. Like a comic book come to life, researchers at Stanford University have developed a kind of Xray vision — only without the X-rays. Working with hardware similar to what enables autonomous cars to “see” the world around them, the researchers enhanced their system with a highly efficient algorithm that can reconstruct three-dimensional hidden scenes based on the movement of photons. In tests, detailed in a paper published Sept...

Dense metallic hydrogen – a phase of hydrogen which behaves like an electrical conductor – makes up the interior of giant planets, but it is difficult to study and poorly understood. By combining artificial intelligence and quantum mechanics, researchers have found how hydrogen becomes a metal under the extreme pressure conditions of these planets.

The researchers, from the University of Cambridge, IBM Research and EPFL, used machine learning to mimic the interactions between hydrogen atoms in order to overcome the size and timescale limitations of even the most powerful supercomputers...

A new ‘global atlas’ study published in Diabetologia (the journal of the European Association for the Study of Diabetes [EASD]) is the first to identify insomnia as a risk factor associated with increased risk of developing type 2 diabetes (T2D). The study identifies 34 risk factors that are thought to increase (19) or decrease risk (15), as well as a further 21 ‘suggestive’ risk factors where evidence was not quite as strong.

The study by Associate Professor Susanna Larsson and by Shuai Yuan of the Karolinska Institutet, Stockholm, Sweden, used a technique called ‘Mendelian Randomisation’ (MR), which uses genetic variation as a natural experiment to investigate the causal relations between potentially modifiable risk factors and health outcomes in observational data...