EVE Online isn't just a game about internet spaceships and sci-fi politics. Since March, developer CCP Games has been running Project Discovery – an initiative to help improve scientific understanding of the human body at the tiniest levels. Run in conjunction with the Human Protein Atlas and Massively Multiplayer Online Science, the project taps into EVE Online's greatest resource – its player base – to help categorise millions of proteins.
"We show them an image, and they can change the colour of it, putting green or red dyes on it to help them analyse it a little bit better," Linzi Campbell, game designer on Project Discovery, tells WIRED. "Then we also show them examples – cytoplasm is their favourite one! We show them what each of the different images should look like, and just get them to pick a few that they identify within the image. The identifications are scrambled each time, so it's not as simple as going 'ok, every time I just pick the one on the right' – they have to really think about it."
The analysis project is worked into EVE Online as a minigame, and works within the context of the game's lore. "We have this NPC organisation called the Drifters – they're like a mysterious entity in New Eden [EVE's interplanetary setting]," Campbell explains. "The players don't know an awful lot about the Drifters at the minute, so we disguised it within the universe as Drifter DNA that they were analysing. I think it just fit perfectly. We branded this as [research being done by] the Sisters of Eve, and they're analysing this Drifter DNA."
The response has been tremendous. "We've had an amazing number of classifications, way over our greatest expectations," says Emma Lundberg, associate professor at the Human Protein Atlas. "Right now, after six weeks, we've had almost eight million classifications, and the players spent 16.2 million minutes playing the minigame. When we did the math, that translated – in Swedish measures – to 163 working years. It's crazy."
"We had a little guess, internally. We said if we get 40,000+ classifications a day, we're happy. If we get 100,000 per day, then we're amazed," Lundberg adds. "But when it peaked in the beginning, we had 900,000 classifications in one day. Now it's stabilised, but we're still getting around 200,000 a day, so everyone is mind-blown. We never expected it."
Resilience, a system’s ability to adjust its activity to retain its basic functionality when errors, failures and environmental changes occur, is a defining property of many complex systems. Despite widespread consequences for human health, the economy and the environment, events leading to loss of resilience—from cascading failures in technological systems to mass extinctions in ecological networks—are rarely predictable and are often irreversible. These limitations are rooted in a theoretical gap: the current analytical framework of resilience is designed to treat low-dimensional models with a few interacting components, and is unsuitable for multi-dimensional systems consisting of a large number of components that interact through a complex network. Here we bridge this theoretical gap by developing a set of analytical tools with which to identify the natural control and state parameters of a multi-dimensional complex system, helping us derive effective one-dimensional dynamics that accurately predict the system’s resilience. The proposed analytical framework allows us systematically to separate the roles of the system’s dynamics and topology, collapsing the behaviour of different networks onto a single universal resilience function. The analytical results unveil the network characteristics that can enhance or diminish resilience, offering ways to prevent the collapse of ecological, biological or economic systems, and guiding the design of technological systems resilient to both internal failures and environmental changes.
BMC Bioinformatics is an open access journal publishing original peer-reviewed research articles in all aspects of the development, testing and novel application of computational and statistical methods for the modeling and analysis of all kinds of biological data, as well as other areas of computational biology. BMC Bioinformatics is part of the BMC series which publishes subject-specific journals focused on the needs of individual research communities across all areas of biology and medicine. We offer an efficient, fair and friendly peer review service, and are committed to publishing all sound science, provided that there is some advance in knowledge presented by the work. BMC series - open, inclusive and trusted.
Dmitry Alexeev's insight:
We published a good research in BMC - next aim is Oxford BI
Average genome size is an important, yet often overlooked, property of microbial communities. We developed MicrobeCensus to rapidly and accurately estimate average genome size from shotgun metagenomic data and applied our tool to 1,352 human microbiome samples. We found that average genome size differs significantly within and between body sites and tracks with major functional and taxonomic differences. In the gut, average genome size is positively correlated with the abundance of Bacteroides and genes related to carbohydrate metabolism. Importantly, we found that average genome size variation can bias comparative analyses, and that normalization improves detection of differentially abundant genes.
Dmitry Alexeev's insight:
well size matters isn't it?
i enjoyed the difference in genome sizes between body habitats
BMC Microbiology is an open access journal publishing original peer-reviewed research articles in analytical and functional studies of prokaryotic and eukaryotic microorganisms, viruses and small parasites, as well as host and therapeutic responses to them, and their interaction with the environment. BMC Microbiology is part of the BMC series which publishes subject-specific journals focused on the needs of individual research communities across all areas of biology and medicine. We offer an efficient, fair and friendly peer review service, and are committed to publishing all sound science, provided that there is some advance in knowledge presented by the work.
Dmitry Alexeev's insight:
somehow missed this work on device for microbiome in vitro cultivation
Background Intestinal microbiota plays an important role in the human health. It is involved in the digestion and protects the host against external pathogens. Examination of the intestinal microbiome interactions is required for understanding of the community influence on host health. Studies of the microbiome can provide insight on methods of improving health, including specific clinical procedures for individual microbial community composition modification and microbiota correction by colonizing with new bacterial species or dietary changes. Methodology/Principal Findings In this work we report an agent-based model of interactions between two bacterial species and between species and the gut. The model is based on reactions describing bacterial fermentation of polysaccharides to acetate and propionate and fermentation of acetate to butyrate. Antibiotic treatment was chosen as disturbance factor and used to investigate stability of the system. System recovery after antibiotic treatment was analyzed as dependence on quantity of feedback interactions inside the community, therapy duration and amount of antibiotics. Bacterial species are known to mutate and acquire resistance to the antibiotics. The ability to mutate was considered to be a stochastic process, under this suggestion ratio of sensitive to resistant bacteria was calculated during antibiotic therapy and recovery. Conclusion/Significance The model confirms a hypothesis of feedbacks mechanisms necessity for providing functionality and stability of the system after disturbance. High fraction of bacterial community was shown to mutate during antibiotic treatment, though sensitive strains could become dominating after recovery. The recovery of sensitive strains is explained by fitness cost of the resistance. The model demonstrates not only quantitative dynamics of bacterial species, but also gives an ability to observe the emergent spatial structure and its alteration, depending on various feedback mechanisms. Visual version of the model shows that spatial structure is a key factor, which helps bacteria to survive and to adapt to changed environmental conditions.
Dmitry Alexeev's insight:
Our first step in Complex System Modelling - done by Tania - MIPT student - the whole dataset is acquired by agent based modelling technique
There are strong genetic components to cardiorespiratory fitness and its response to exercise training. It would be useful to understand the differences in the genomic profile of highly trained endurance athletes of world class caliber and sedentary controls. An international consortium (GAMES) was established in order to compare elite endurance athletes and ethnicity-matched controls in a case-control study design. Genome-wide association studies were undertaken on two cohorts of elite endurance athletes and controls (GENATHLETE and Japanese endurance runners), from which a panel of 45 promising markers was identified. These markers were tested for replication in seven additional cohorts of endurance athletes and controls: from Australia, Ethiopia, Japan, Kenya, Poland, Russia and Spain. The study is based on a total of 1520 endurance athletes (835 who took part in endurance events in World Championships and/or Olympic Games) and 2760 controls. We hypothesized that world-class athletes are likely to be characterized by an even higher concentration of endurance performance alleles and we performed separate analyses on this subsample. The meta-analysis of all available studies revealed one statistically significant marker (rs558129 at GALNTL6 locus, p = 0.0002), even after correcting for multiple testing. As shown by the low heterogeneity index (I 2 = 0), all eight cohorts showed the same direction of association with rs558129, even though p-values varied across the individual studies. In summary, this study did not identify a panel of genomic variants common to these elite endurance athlete groups. Since GAMES was underpowered to identify alleles with small effect sizes, some of the suggestive leads identified should be explored in expanded comparisons of world-class endurance athletes and sedentary controls and in tightly controlled exercise training studies. Such studies have the potential to illuminate the biology not only of world class endurance performance but also of compromised cardiac functions and cardiometabolic diseases.
Dmitry Alexeev's insight:
Largest study so far - we had no chances to have power enough for that - it is just because eilte athletes are elite)
Brain Blogger (blog) The Brain-Gut Axis, Part 3 – The Gut Microbiota In Disease Brain Blogger (blog) In Part 2 of the brain-gut axis article series, I explained how the brain and the gut microbiota communicate.
The determination of the most central agents in complex networks is important because they are responsible for a faster propagation of information, epidemics, failures and congestion, among others. A challenging problem is to identify them in networked systems characterized by different types of interactions, forming interconnected multilayer networks. Here we describe a mathematical framework that allows us to calculate centrality in such networks and rank nodes accordingly, finding the ones that play the most central roles in the cohesion of the whole structure, bridging together different types of relations. These nodes are the most versatile in the multilayer network. We investigate empirical interconnected multilayer networks and show that the approaches based on aggregating—or neglecting—the multilayer structure lead to a wrong identification of the most versatile nodes, overestimating the importance of more marginal agents and demonstrating the power of versatility in predicting their role in diffusive and congestion processes.
Ranking in interconnected multilayer networks reveals versatile nodes Manlio De Domenico, Albert Solé-Ribalta, Elisa Omodei, Sergio Gómez & Alex Arenas
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