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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.

Vesper

VESpeR is a suite of web-based visualisation components that enable biologists to investigate the taxonomic, temporal and geographic coverage of DWCA species-referenced data that can be placed directly into the workflow of biologists who use such data. VESpeR allows biologists to perform tasks such as sanity checking of data, view patterns in geographical, taxonomic or temporal aspects in an interrelated context, and accurately view data even when it spans conflicting taxonomic classifications. This can make a significant contribution to the efficiency and usability of online catalogues for both the providers and end-users of the data they hold. Co-ordinated components The components are co-ordinated such that selections and actions in one component will be reflected in the data shown in other components. VESpeR multiple views VESpeR includes

  • a novel cross-taxonomy viewer that allows users to crosswalk different classifications, allowing them to accurately match specimens between data from different sources
  • interactive map to investigate specimen geographic coverage
  • interactive timeline to investigate specimen temporal coverage
  • sanity checker to view data completeness and vocabulary size

Bio-visualisation Visualisation techniques have been recognised as one of the major directions in future research when handling and querying biological data, offering the ability to find patterns and outliers in data which traditional query interfaces cannot match. A case in point is the multitude of species-referenced databases covering data from genomic to biodiversity data linked by taxonomic classifications that hold geographic and temporal-faceted data alongside other data. Many online databases hold collections of such data, often in archive format, but visual querying tools are invariably limited to a map interface of spatial distribution, neglecting the fact that biologists may wish to query or explore other facets of the data such as the classification or temporal distribution. Add onto this the problem of many complementary databases using different taxonomic classifications to reference their specimens and we have a situation where much of the potential utility of this data remains unused. VESpeR is designed to help address this.

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Institution: IIDI

VESpeR is a project at the Institute for Informatics and Digital Innovation. The Institute is part of Edinburgh Napier University based in Scotland, United Kingdom. At the Institute for Informatics & Digital Innovation we are dedicated to helping you and your organisation deal with new digital challenges and opportunities as they arise. We can help you to look ahead and shape our digital future. We work across every field of computer technology from sensors and mobile networks to data intensive applications requiring intelligent processing and filtering. We can help you explore not just the technology but how people interact with the technology and how it impacts on society. www.iidi.napier.ac.uk Tel: +44 (0)131 455 2651 Email: iidi@napier.ac.uk

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