Scientists are using machine learning to interpret “dark matter” DNA

Scientists at Gladstone Institutes are using machine learning to target genetic disorders in so-called genomic “dark matter”.

The computational method being used, called TargetFinder, predicts where non-coding DNA – the DNA that does not code for proteins – interacts with genes. By analysing big data, researchers are abble to connect mutations in genomic “dark matter” with the genes they affect, potentially revealing new targets for genetic disorders.

In the study, published in Nature Genetics, the team from Gladstone Institutes looked at fragments of non-coding DNA called enhancers which act like an instruction manual for a gene, dictating when and where a gene is turned on.

“Most genetic mutations that are associated with disease occur in enhancers, making them an incredibly important area of study,” said the study’s senior author, Katherine Pollard. “Before now, we struggled to understand how enhancers find the distant genes they act upon.”

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The new study revealed that, on a strand of DNA, enhancers can be millions of letters away from the gene they influence.

However, using machine learning technology, the researchers were able to analyse hundreds of existing datasets to look for patterns in the genome and identify where a gene and enhancer interact.

They discovered that when an enhancer is far away from the gene it affects, the two connect by forming a three-dimensional loop, like a bow on the genome.

“It’s remarkable that we can predict complex three-dimensional interactions from relatively simple data,” said biostatistician at Gladstone, Sean Whalen. “No one had looked at the information stored on loops before, and we were surprised to discover how important that information is.”

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The new computational approach is a much cheaper and a less time-consuming way to identify gene-enhancer connections in the genome as performing experiments in the can take millions of dollars and years of research.

The technology also gives an insight into how DNA loops form and how they might break in disease.

“Our ability to predict the gene targets of enhancers so accurately enables us to link mutations in enhancers to the genes they target,” said Pollard. “Having that link is the first step towards using these connections to treat diseases.”

Gladstone is set to offer all of the code and data from TargetFinder online for free.

Robot takes first steps towards building artificial lifeforms

A robot equipped with sophisticated AI has successfully simulated the creation of artificial lifeforms, in a key first step towards the eventual goal of creating true artificial life.

The robot, which was developed by scientists at the University of Glasgow, was able to model the creation of artificial lifeforms using unstable oil-in-water droplets. These droplets effectively played the role of living cells, demonstrating the potential of future research to develop living cells based on building blocks that cannot be found in nature.

Significantly, the robot also successfully predicted their properties before they were created, even though this could not be achieved using conventional physical models.

The robot, which was designed by Glasgow University’s Regius Chair of Chemistry, Professor Lee Cronin, is driven by machine learning and the principles of evolution.

It has been developed to autonomously create oil-in-water droplets with a host of different chemical makeups and then use image recognition to assess their behaviour.

Using this information, the robot was able to engineer droplets to have different properties­. Those which were found to be desirable could then be recreated at any time, using a specific digital code.

“This work is exciting as it shows that we are able to use machine learning and a novel robotic platform to understand the system in ways that cannot be done using conventional laboratory methods, including the discovery of ‘swarm’ like group behaviour of the droplets, akin to flocking birds,” said Cronin.

“Achieving lifelike behaviours such as this are important in our mission to make new lifeforms, and these droplets may be considered ‘protocells’ – simplified models of living cells.”

One of the oil droplets created by the robot

The research, which is published today in the journal PNAS, is one of several research projects being undertaken by Cronin and his team within the field of artificial lifeforms.

While the overarching goal is moving towards the creation of lifeforms using new and unprecedented building blocks, the research may also have more immediate potential applications.

The team believes that their work could also have applications in several practical areas, including the development of new methods for drug delivery or even innovative materials with functional properties.

Mac spyware stole millions of user images

A criminal case brought against a man from Ohio, US has shed more light on a piece of Mac malware, dubbed Fruitfly, that was used to surreptitiously turn on cameras and microphones, take and download screenshots, log keystrokes, and steal tax and medical records, photographs, internet searches, and bank transactions from users.

Source: Ars Technica

Drone swarm attack strikes Russian military bases

Russia's Ministry of Defence claims its forces in Syria were attacked a week ago by a swarm of home-made drones. According to Russia's MoD Russian forces at the Khmeimim air base and Tartus naval facility "successfully warded off a terrorist attack with massive application of unmanned aerial vehicles (UAVs)"

Source: Science Alert

Las Vegas strip club employs robot strippers

A Las Vegas strip club has flown in robot strippers from London to 'perform' at the club during CES. Sapphire Las Vegas strip club managing partner Peter Feinstein said that he employed the robots because the demographics of CES have changed and the traditional female strippers aren’t enough to lure a crowd to the club anymore.

Source: Daily Beast

GM to make driverless cars without steering wheels or pedals by 2019

General Motors has announced it plans to mass-produce self-driving cars without traditional controls like steering wheels and pedals by 2019. “It’s a pretty exciting moment in the history of the path to wide scale [autonomous vehicle] deployment and having the first production car with no driver controls,” GM President Dan Ammann told The Verge.

Source: The Verge

Russia-linked hackers "Fancy Bears" target the IOC

Following Russia's ban from the upcoming 2018 Winter Olympics, the Russia-linked hacking group "Fancy Bears" has published a set of apparently stolen emails, which purportedly belong to officials from the International Olympic Committee, the United States Olympic Committee, and third-party groups associated with the organisations.

Source: Wired

Scientists discover ice cliffs on Mars

Using images provided by the Mars Reconnaissance Orbiter, scientists have described how steep cliffs, up to 100 meters tall, made of what appears to be nearly pure ice indicate that large deposits of ice may also be located in nearby underground deposits. The discovery has been described as “very exciting” for potential human bases.

Source: Science Mag