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How playing games can help scientific research

Ever felt that saving princess Zelda or “catching ‘em all” was not rewarding enough? If so, why don’t you help Science and play serious games? In their wider definition, serious games are games designed for other purposes than pure entertainment. In scientific research, serious games have been developed to make the community of gamers participate in the resolution of complex problems that cannot be solved by machines. Serious games in biomedical research Indeed, humans are very efficient at recognising patterns, which is rather a difficult task for computers and algorithms. Serious games combine a pleasing interface, a challenging and entertaining problem to solve, and a will to help scientific research.  Problem to solve can be broke down into smaller tasks, …

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Map functional networks of ncRNAs with circlncRNAnet

Long non-coding RNAs (lncRNAs) and circular RNAs (circRNAs) lack protein-coding potential but have nonetheless emerged as key determinants in gene regulation, acting to fine-tune transcriptional and signaling output. These noncoding RNA transcripts are known to affect expression of messenger RNAs (mRNAs) via epigenetic and post-transcriptional regulation. To fully capture, from a network perspective, the functional implications of lncRNAs or circRNAs of interest, Dr. Bertrand Chin-MingTan and his team have implemented an integrative bioinformatics approach to examine in silico the functional networks of non-coding RNAs. Here, they present their web server tool “circlncRNAnet” and discuss its main features. In-depth analyses of non-coding RNA biology The main purpose for implementing this web server is to provide biologists with a user-friendly, “one-stop” web tool …

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Simulate immune responses to vaccines with C-IMMSIM

Because of the diversity of the immune repertoires, it is very challenging to predict the efficacy of a vaccine to properly stimulate all components of the immune system and ultimately protect against infectious diseases, that is it’s immunogenicity. To aid researchers in the design and set up of their vaccination/infection protocols, Dr. Filippo Castiglione and colleagues from the Institute for Applied Computing in Rome have developed C-IMMSIM. Here, he talks about the features and benefits of his tool. A novel and free tool to perform in silico experiments about vaccinations and/or infections To date, this is the only simulation tool for the immune response which combines epitope/peptide prediction algorithms with agent-based methodology to predict the follow-up of virtual infection experiments. …

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Write a review and enter to win exciting prizes!

Do you use specific tools to analyze your biomedical data? Offer your feedback on the tools we reference and enter to win a set of headphones and gift cards! To participate, all you need to do is provide your opinion on the performance of the tools which you routinely use. The contest is open until the 4 February. How does the contest work? Sign in to your account (or sign up for free if you aren’t already a member). Locate your favorite tools: use the search engine and filters to rapidly locate your tools. Click on “write a review” to give it a rating and provide your feedback. Why is your review important? Reviews offer a double advantage. As a …

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Predict transcription factor binding from DNase footprints with Sasquatch

Predicting the impact of regulatory sequence variation on transcription factor (TF) binding is an important challenge as the vast majority of disease associated SNPs are found in the non-coding genome (Vaquerizas, Kummerfeld, Teichmann, & Luscombe, 2009)⁠. Most existing approaches rely on large catalogs of cell type and TF specific functional annotations. As only a minority of TFs is well characterized (Maurano et al., 2015; Rockman & Kruglyak, 2006)⁠, identifying the relevant factors and probing them in the appropriate cell types represents a major limitation of TF centric approaches. With this in mind, Ron Schwessinger and colleagues from University of Oxford have developed the Sasquatch tool to use DNase footprinting data to estimate and visualize the effects of non-coding variants on …

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Identify and map genomic islands with xenoGI

Genomic islands (GI) are part of a genome that have been transferred horizontally beween organisms, typically bacteria. They code for many functions, such as symbiosis, pathogenesis, antibiotic resistance, etc. Determining GI is often performed by base composition analysis and phylogeny estimations.   Dr. Eliot Bush has developed xenoGI, a tool that proposes several features to aid identify islands of genes that entered via common horizontal transfer events, to map those events onto the phylogenetic tree, and more. Here, he briefly describes the features and benefits of his tool. Features and benefits of xenoGI Microbes have acquired many important traits through the horizontal transfer of genomic islands. Understanding the evolution of these traits often requires us to understand the adaptive path …

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Towards standardized protocols for microbiome studies

The study of the microbiome – that is, the ensemble of microbial communities living inside us – has become a major application for high-throughput DNA sequencing. Functional changes in the composition of the gut microbiome have been implicated in multiple human diseases. Due to its complexity, the analysis of sequencing data from microbiome study typically involves a lot of different protocols and bioinformatics tools. From sample collection and DNA extraction to sequencing and computational analysis, technical errors and bias can occur at each step, rendering the uniformization of protocols a complex task. To this end, two consortia recently proposed to examine the sources of inter-laboratory variability in various aspects of microbiome data generation. This work was published in the last …

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Process 16S rRNA sequences with the sl1p tool

Advancing DNA sequencing technologies have encouraged a surge of microbiome studies. The microbiome, the set of microbes (bacteria, viruses, archaea) who live in a particular environmental niche, has been extensively studied, including in the context of human disease, changes in ecological environments, and progressive oxygen gradients in the deep sea. One of the most popular methods for these types of studies is the sequencing of segments of the 16S rRNA gene– a highly conserved gene among bacterial populations which allows researchers to identify the taxonomic diversity within a given bacterial niche. Drs. Whelan and Surette have recently come up with a new tool, sl1p, that helps automate the processing of 16S rRNA gene sequencing data and provides analyses which allow the …

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