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Domain: ploscompbiol.org
Stories and comments across the archive that link to ploscompbiol.org.
Stories · 10
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Researchers Forecast the Spread of Diseases Using Wikipedia
An anonymous reader writes Scientists from Los Alamos National Laboratory have used Wikipedia logs as a data source for forecasting disease spread. The team was able to successfully monitor influenza in the United States, Poland, Japan, and Thailand, dengue fever in Brazil and Thailand, and tuberculosis in China and Thailand. The team was also able to forecast all but one of these, tuberculosis in China, at least 28 days in advance. -
New Links Found Between Bacteria and Cancer
Shipud writes "A recent study by a group at the University of Maryland School of Medicine shows that bacterial DNA gets transferred to human cells, in a process known as lateral gene transfer, or LGT. LGT is known to occur quite commonly between bacteria, including bacteria of different species. In fact, that is how antibiotic resistance is transferred so quickly. The team has shown that certain types of tumor cells acquire bacterial DNA that may play a role in tumor progression. Another group at the University of North Carolina, Chapel Hill has shown that gut inflammation leads to a radical change in the microbial population there, which encourages growth of E. coli that can disrupt the inflamed cells' DNA, leading to cancer. Both studies enable us to ask new questions such as: how does inflammation change the landscape for bacterial colonization? Can bacteria indeed harness inflammation — and then cancer — to flourish and remove competitors from their newly found ecosystem? And can we use this information to fight cancer?" -
Stanford Researchers Discover the 'Anternet'
stoilis writes "A collaboration between Deborah Gordon, a Stanford ant biologist, and Balaji Prabhakar, a computer scientist, has revealed that the behavior of harvester ants, as they forage for food, mirrors the protocols that control traffic on the Internet. From the article: 'Prabhakar wrote an ant algorithm to predict foraging behavior depending on the amount of food – i.e., bandwidth – available. Gordon's experiments manipulate the rate of forager return. Working with Stanford student Katie Dektar, they found that the TCP-influenced algorithm almost exactly matched the ant behavior found in Gordon's experiments. "Ants have discovered an algorithm that we know well, and they've been doing it for millions of years," Prabhakar said.' The abstract is published in the Aug. 23 issue of PLoS Computational Biology." -
Computers May Be As Good As (Or Better Than) Human Biocurators
Shipud writes "Sequencing the genome of an organism is not the end of a discovery process; rather, it is a beginning. It's the equivalent of discovering a book whose words (genes) are there, but their meaning is yet unknown. Biocurators are the people who annotate genes — find out what they do — through literature search and the supervised use of computational techniques. A recent study published in PLoS Computational Biology shows that biocurators probably perform no better than fully automated computational methods used to annotate genes. It is not clear whether this is because the software is of high quality, or both curators and software need to improve their performance. The author of this blog post uses the concept of the uncanny valley to explain this recent discovery and what it means to both life science and artificial intelligence." -
Researchers Use Google's Search Algorithms To Fight Cancer
MatthewVD writes "German scientists have modified Google's PageRank algorithm to scan tumors and learn more about how cancers progress. PageRank orders results based on how other web pages are connected to them via hyperlinks; the modified algorithm, NetRank, scans how genes and proteins in a cell are similarly connected through a network of interactions with their neighbors. This approach could also yield new therapies to help combat tumors." -
MIT & Harvard On Brain-Inspired A.I. Vision
An anonymous reader writes with this excerpt from TGDaily: "Researchers from Harvard and MIT have demonstrated a way to build better artificial visual systems with the help of low-cost, high-performance gaming hardware. [A video describing their research is available.] 'Reverse engineering a biological visual system — a system with hundreds of millions of processing units — and building an artificial system that works the same way is a daunting task,' says David Cox, Principal Investigator of the Visual Neuroscience Group at the Rowland Institute at Harvard. 'It is not enough to simply assemble together a huge amount of computing power. We have to figure out how to put all the parts together so that they can do what our brains can do.' The team drew inspiration from screening techniques in molecular biology, where a multitude of candidate organisms or compounds are screened in parallel to find those that have a particular property of interest. Rather than building a single model and seeing how well it could recognize visual objects, the team constructed thousands of candidate models, and screened for those that performed best on an object recognition task. The resulting models outperformed a crop of state-of-the-art computer vision systems across a range of test sets, more accurately identifying a range of objects on random natural backgrounds with variation in position, scale, and rotation. Using ordinary CPUs, the effort would have required either years or millions of dollars of computing hardware. Instead, by harnessing modern graphics hardware, the analysis was done in just one week, and at a small fraction of the cost." -
The Math of a Fly's Eye May Prove Useful
cunniff writes "Wired Magazine points us to recent research that demonstrates an algorithm derived from the actual biological implementation of fly vision (PLoS paper here). Quoting the paper: 'Here we present a model with multiple levels of non-linear dynamic adaptive components based directly on the known or suspected responses of neurons within the visual motion pathway of the fly brain. By testing the model under realistic high-dynamic range conditions we show that the addition of these elements makes the motion detection model robust across a large variety of images, velocities and accelerations.' The researchers claim that 'The implementation of this new algorithm could provide a very useful and robust velocity estimator for artificial navigation systems.' Additionally, the paper describes the algorithm as extremely simple, capable of being implemented on very small and power-efficient processors. Best of all, the entire paper is public and hosted via a service that allows authenticated users to give feedback." -
PageRank Algorithm Applied To the Food Web
An anonymous reader brings word of a new application for PageRank, Google's link analysis algorithm: monitoring the food web in an ecosystem. A team of researchers found that a modified version of PageRank can predict with great accuracy which species are vital to the existence of others. Quoting: "Every species is embedded in a complex network of relationships with others. A single extinction can cascade into the loss of seemingly unrelated species. Investigating when this might happen using more conventional methods is complicated, as even in simple ecosystems, the number of combinations exceeds the number of atoms in the universe. So, it would be impossible to try them all. Co-author Dr. Stefano Allesina realized he could apply PageRank to the problem when he stumbled across an article in a journal of applied mathematics describing the Google algorithm. 'First of all, we had to reverse the definition of the algorithm. In PageRank, a web page is important if important pages point to it. In our approach, a species is important if it points to important species.'" -
Open-Access Computational Biology Journal Launches
FleaPlus writes "The Public Library of Science and International Society for Computational Biology have published the inaugural issue of PLoS Computational Biology, an open-access journal dedicated to studies which 'further our understanding of living systems at all scales through the application of computational methods.' All works published in the journal are to be released under a Creative Commons Attribution License. The founding editors have some comments on the launch." -
Two New PLoS Journals Launched
Shipud writes "The Public Library of Science journal series is expanding. After PLoS biology and PLoS Medicine we are now getting a geek's favorite: PLoS Computational Biology. Another addition is PLoS Genetics. Both are published open-access under the creative commons license. A history of open access licence publications in science can be found here."