Automated protein function prediction is a challenging problem with distinctive features, such as the hierarchical organization of protein functions and the scarcity of annotated proteins for most biological functions. We propose a multitask learning algorithm addressing both issues. Unlike standard multitask algorithms, which use task (protein functions) similarity information as a bias to speed up learning, we show that dissimilarity information enforces separation of rare class labels from frequent class labels, and for this reason is better suited for solving unbalanced protein function prediction problems. We support our claim by showing that a multitask extension of the label propagation algorithm empirically works best when the task relatedness information is represented using a dissimilarity matrix as opposed to a similarity matrix. Moreover, the experimental comparison carried out on three model organism shows that our method has a more stable performance in both "protein-centric" and "function-centric" evaluation settings.

Using Azure, gave them an immediate global reach in a way unthinkable just a few years earlier. Their mission is to bring big data analytics to utilities and smart cities, and one of their focus areas is electric utilities and smart grids. It is a story that combines drones with intelligent software to prevent power blackouts, or as eSmart puts it "making Azure intelligence mobile". The economic impact of blackouts is massive, and the scale of power grids is huge. According to Grid Resilience Report, US Department of Energy, 2011, the average annual cost of power outages caused by severe weather in the USA is anywhere between $18-33 billion.

There is no shortage of attention lately on the "Internet of Things". As a case in point, see the "Developing Innovation and Growing the Internet of Things Act" or "DIGIT Act", i.e., S. 2607, a bill introduced in the Senate on March 1, 2016 and amended on September 28, 2016, "to ensure appropriate spectrum planning and inter-agency coordination to support the Internet of Things" – A companion bill, H.R. 5117, was introduced in the House of Representatives on April 28, 2016. However, since there is no "internet" dedicated to "things", it is fair to state that the Internet of Things does not exist as such. We are left with a definitional vacuum, but it is hammering the obvious to acknowledge that there is no dearth of attempts around the world to fill the gap. Perhaps as a helpful shortcut, we could view the expression as a metaphor that captures the arrival of almost anything and everything, until now out of scope, into the communications space.

WASHINGTON – Donald Trump blames Mexico and China for stealing millions of jobs from the United States. Despite the Republican presidential nominee's charge that "we don't make anything anymore," manufacturing is still flourishing in America. Problem is, factories don't need as many people as they used to because machines now do so much of the work. America has lost more than 7 million factory jobs since manufacturing employment peaked in 1979. Yet American factory production, minus raw materials and some other costs, more than doubled over the same span to $1.91 trillion last year, according to the Commerce Department, which uses 2009 dollars to adjust for inflation.

Aberdeen Bestiary's secrets revealed: 800-year-old book owned by Henry VIII was a learning tool seized during the dissolution of the monasteries New digitally enhanced photography of the book, known as the'Aberdeen Bestiary', has revealed previously unknown secrets behind the scripture A blank page in the Aberdeen Bestiary's twin manuscript, Ashmole 1511, this page is occupied by scenes concerning the lion shown left. This page shown left was probably intended for scenes about the lion, the researchers said. Experts have long debated whether the Bestiary, which is lavishly illustrated in gold leaf, was commissioned for a high-status client or seized during Henry's reign from a dissolved monastic library Professor Jane Geddes, an art historian at Aberdeen University, says marks and annotations that were not previously visible point to the book having been handpicked by Henry's scouts when they scoured monasteries for valuables Professor Geddes added: 'On many of the words there are tiny marks which would have provided a guide to the correct pronunciation when the book was being read aloud. The views expressed in the contents above are those of our users and do not necessarily reflect the views of MailOnline. By posting your comment you agree to our house rules.

Machine learning, which is the basis for most commercial artificial-intelligence systems, is intrinsically probabilistic. An object-recognition algorithm asked to classify a particular image, for instance, might conclude that it has a 60 percent chance of depicting a dog, but a 30 percent chance of depicting a cat. At the Annual Conference on Neural Information Processing Systems in December, MIT researchers will present a new way of doing machine learning that enables semantically related concepts to reinforce each other. So, for instance, an object-recognition algorithm would learn to weigh the co-occurrence of the classifications "dog" and "Chihuahua" more heavily than it would the co-occurrence of "dog" and "cat." In experiments, the researchers found that a machine-learning algorithm that used their training strategy did a better job of predicting the tags that human users applied to images on the Flickr website than it did when it used a conventional training strategy.

Artificial intelligence can thank Hollywood for its bad rep. Movies like "Ex Machina" and the "Terminator" series conjure up futuristic doomsday scenarios where intelligent machines wreak havoc on humans. However, in real life, humans are already surrounded by artificial intelligence. Amazon and Netflix recommendation engines suggest books or movies based on previous selections, Google Now reroutes drivers around traffic accidents on the commute home, and smartphone digital assistants like Apple's Siri and Microsoft's Cortana answer questions about the weather and sports scores. Brands are using artificial intelligence to build better customer experiences and they're just getting started.

Oren Etzioni, a well-known AI researcher, complains about news coverage of potential long-term risks arising from future success in AI research (see "Are Experts Worried About the Existential Risk of Artificial Intelligence?"). After pointing the finger squarely at Oxford philosopher Nick Bostrom and his recent book, Superintelligence, Etzioni complains that Bostrom's "main source of data on the advent of human-level intelligence" consists of surveys on the opinions of AI researchers. He then surveys the opinions of AI researchers, arguing that his results refute Bostrom's. It's important to understand that Etzioni is not even addressing the reason Superintelligence has had the impact he decries: its clear explanation of why superintelligent AI may have arbitrarily negative consequences and why it's important to begin addressing the issue well in advance. Bostrom does not base his case on predictions that superhuman AI systems are imminent.

Some eagles could soon be spending much of their life in jail if the U.K. government gets its way. No, the powers-that-be aren't looking to target the majestic creature in some kind of bizarre police crackdown on bird-instigated crime. Instead, it's hoping to make use of their supreme hunting skills in its fight to keep drone-delivered contraband out of the nation's prisons. Discussing the issue during a debate in the British parliament this week, prisons minister Sam Gyimah described the threat posed by drones as "a game changer," adding that the government was looking for an effective solution for dealing with rogue unmanned flying machines around prisons and other sensitive locations. Gyimah said his team was "keeping a close eye on what's happening in Holland, where they're using eagles to stop drones." Police in the Netherlands recently completed extensive trials using highly trained eagles to snatch remotely controlled multi-rotor copters out of the sky and return them to their handler.

They're not driven by the unknown, but by the present. Let's look at the last epoch-changing technological development: the internet. The tech utopians of the late 20th century saw the incoming digital revolution as a liberating force, one that would dismantle the old power structures that oppress us and help humanity build a new, more perfect society. It's painfully clear now that their hypothesis was laughably naive. Who, exactly, has the internet liberated? Silicon Valley tech tycoons and advertisers aside, it has decimated the music, film and publishing industries, slashed the earnings of musicians, writers, photographers, and just about every other professional whose product can be digitized, shrinking their industries, killing off job openings, and maiming job security.