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GVF Alignment Viz

By applying gradient vector flow analysis to the MSA data, it is possible to extract and visually emphasize conservations and other patterns that are relevant during the MSA exploration process. In contrast to the traditional visual representation of MSAs, which exploits color-coded tables, the proposed visual metaphor allows us to provide an overview of large MSAs as well as to highlight global patterns, outliers, and data distributions.

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Institution: Linkoping University, Sweden

This work was supported through grants from the Excellence Center at Linkoping and Lund in Information Technology (ELLIIT), the Swedish Research Council (VR, grant 2011–4113), and the Swedish e-Science Research Centre (SeRC). The presented technique has been integrated into the Voreen volume rendering engine (www.voreen.org), which is an open source visualization framework.

PresentaBALL

PresentaBALL is a presentation framework which uses established web technology standards to provide a freely configurable browser-based interface into the extensive modeling and visualization capabilities of the Biochemical Algorithms Library (BALL). This allows easy yet powerful dissemination of structure based research results at conferences or trade fairs, the preparation of lectures, or the development of massive open online courses (MOOCs)

The web interface is embedded into BALL's graphical frontend BALLView, and provides complete, interactive access to the loaded molecular data.

PresentaBALL enables researchers in biology with basic knowledge in HTML, JavaScript, or Python to easily setup academic tutorials, demonstrations, or scientific presentations and lectures with 3D structure content and interactive workflows. Owing to its flexible design, other modern forms of teaching and presentation, such as massive open online courses (MOOC) can also use PresentaBALL as their core component.

PresentaBALL is licensed under the GNU Public License (GPL) and will be made available in BALL/BALLView, starting with the upcoming release.

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Institution: Center for Bioinformatics, Saarland University, Johannes-Gutenberg-University Mainz, Intel Visual Computing Institute, Saarland University

rNAV

rNAV (for rna NAVigator) is a tool for the visual exploration and analysis of bacterial sRNA-mediated regulatory networks. rNAV has been designed to help bioinformaticians and biologists to identify, from lists of thousands of predictions, pertinent and reasonable sRNA target candidates for carrying out experimental validations.

We now propose an automatic mRNAs extraction from a simple genbank or embl genome file. Moreover, rNAV now features an automatic annotation enrichement plugin powered by DAVID statistical enrichement tool.
rNAV algorithms can be gathered into pipelines which can then be saved and reused over several sessions. To support exploration awareness, rNAV also provides an exploration tree view that allows to navigate through the steps of the analysis but also to select the sub-networks to visualize and compare. These comparisons are facilitated by the integration of multiple and fully linked views.

This framework had been used to analyse various real biological data including several mycoplasma strains.

Some key features :

  • Automatic functional annotation with DAVID[1] webservice (Database for Annotation, Visualization and Integrated Discovery)
  • Annotation clustering : cluster redudant annotations
  • Simultaneous visual analysis of annotations AND positions of several targets with enhanced neighbors tool.
  • Visual analysis of sRNA regulatory networks at genome scale
  • Automatic mRNA extraction from genome files (genbank or embl) with user defined region
  • Integration of two interactions prediction tools : ssearch and IntaRNA[2]
  • Position clustering : cluster targets from their interaction positions
  • Multiple and fully linked view
  • Exploration tree view
  • Labels can display many input information like P-value, Similarity or interaction energy
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Institution: Universite Bordeaux 1, Universite Bordeaux 2, Universite Paris 7, ANR (France)

This work was partially done under the EVIDEN project (ANR 2010 JCJC 0201 01), supported by the ANR (France); and under the MycoRNA project, PEPS CNRS/IdEx Bordeaux, 2013.

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