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DASS-GUI : a user interface for identification and analysis of significant patterns in non-sequential data

(2010) BIOINFORMATICS. 26(7). p.987-989
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Abstract
Many large 'omics' datasets have been published and many more are expected in the near future. New analysis methods are needed for best exploitation. We have developed a graphical user interface (GUI) for easy data analysis. Our discovery of all significant substructures (DASS) approach elucidates the underlying modularity, a typical feature of complex biological data. It is related to biclustering and other data mining approaches. Importantly, DASS-GUI also allows handling of multi-sets and calculation of statistical significances. DASS-GUI contains tools for further analysis of the identified patterns: analysis of the pattern hierarchy, enrichment analysis, module validation, analysis of additional numerical data, easy handling of synonymous names, clustering, filtering and merging. Different export options allow easy usage of additional tools such as Cytoscape.
Keywords
PROTEIN SUBCOMPLEXES, ALIGNMENT

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Citation

Please use this url to cite or link to this publication:

Chicago
Hollunder, Jens, Maik Friedel, Martin Kuiper, and Thomas Wilhelm. 2010. “DASS-GUI : a User Interface for Identification and Analysis of Significant Patterns in Non-sequential Data.” Bioinformatics 26 (7): 987–989.
APA
Hollunder, J., Friedel, M., Kuiper, M., & Wilhelm, T. (2010). DASS-GUI : a user interface for identification and analysis of significant patterns in non-sequential data. BIOINFORMATICS, 26(7), 987–989.
Vancouver
1.
Hollunder J, Friedel M, Kuiper M, Wilhelm T. DASS-GUI : a user interface for identification and analysis of significant patterns in non-sequential data. BIOINFORMATICS. 2010;26(7):987–9.
MLA
Hollunder, Jens, Maik Friedel, Martin Kuiper, et al. “DASS-GUI : a User Interface for Identification and Analysis of Significant Patterns in Non-sequential Data.” BIOINFORMATICS 26.7 (2010): 987–989. Print.
@article{947388,
  abstract     = {Many large 'omics' datasets have been published and many more are expected in the near future. New analysis methods are needed for best exploitation. We have developed a graphical user interface (GUI) for easy data analysis. Our discovery of all significant substructures (DASS) approach elucidates the underlying modularity, a typical feature of complex biological data. It is related to biclustering and other data mining approaches. Importantly, DASS-GUI also allows handling of multi-sets and calculation of statistical significances. DASS-GUI contains tools for further analysis of the identified patterns: analysis of the pattern hierarchy, enrichment analysis, module validation, analysis of additional numerical data, easy handling of synonymous names, clustering, filtering and merging. Different export options allow easy usage of additional tools such as Cytoscape.},
  author       = {Hollunder, Jens and Friedel, Maik and Kuiper, Martin and Wilhelm, Thomas},
  issn         = {1367-4803},
  journal      = {BIOINFORMATICS},
  language     = {eng},
  number       = {7},
  pages        = {987--989},
  title        = {DASS-GUI : a user interface for identification and analysis of significant patterns in non-sequential data},
  url          = {http://dx.doi.org/10.1093/bioinformatics/btq071},
  volume       = {26},
  year         = {2010},
}

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