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R. S. WebTool, a web server for random sampling-based significance evaluation of pairwise distances

Title
R. S. WebTool, a web server for random sampling-based significance evaluation of pairwise distances
Authors
Villiers, F[Villiers, Florent]Bastien, O[Bastien, Olivier]Kwak, JM[Kwak, June M.]
DGIST Authors
Kwak, JM[Kwak, June M.]
Issue Date
2014-07-01
Citation
Nucleic Acids Research, 42(W1), W198-W204
Type
Article
Article Type
Article
ISSN
0305-1048
Abstract
Pairwise comparison of data vectors represents a large part of computational biology, especially with the continuous increase in genome-wide approaches yielding more information from more biological samples simultaneously. Gene clustering for function prediction as well as analyses of signalling pathways and the time-dependent dynamics of a system are common biological approaches that often rely on large dataset comparison. Different metrics can be used to evaluate the similarity between entities to be compared, such as correlation coefficients and distances. While the latter offers a more flexible way of measuring potential biological relationships between datasets, the significance of any given distance is highly dependent on the dataset and cannot be easily determined. Monte Carlo methods are robust approaches for evaluating the significance of distance values by multiple random permutations of the dataset followed by distance calculation. We have developed R. S. WebTool (http://rswebtool.kwaklab.org), a user-friendly online server for random sampling-based evaluation of distance significances that features an array of visualization and analysis tools to help non-bioinformaticist users extract significant relationships from random noise in distance-based dataset analyses.
URI
http://hdl.handle.net/20.500.11750/3072
DOI
10.1093/nar/gku427
Publisher
Oxford University Press
Related Researcher
  • Author Kwak, June Myoung KWAK_LAB(Lab of Cell Signailng)
  • Research Interests Calcium Signaling; ABA;ROS Signaling; drought-tolerant plants; Development of Abscission; Culluar Features; Signaling network; Environmental Regulation
Files:
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Collection:
New BiologyETC1. Journal Articles


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