A web2.0 strategy for the collaborative analysis of complex bioimages

  • Authors:

  • Christian Loyek;Jan Kölling;Daniel Langenkämper;Karsten Niehaus;Tim W. Nattkemper

  • Affiliations:

  • Biodata Mining Group, Faculty of Technology, Bielefeld University, Germany;Biodata Mining Group, Faculty of Technology, Bielefeld University, Germany;Biodata Mining Group, Faculty of Technology, Bielefeld University, Germany;Genome Research and Systems Biology, Proteome and Metabolome Research, Bielefeld University, Germany;Biodata Mining Group, Faculty of Technology, Bielefeld University, Germany

  • Venue:
  • IDA'11 Proceedings of the 10th international conference on Advances in intelligent data analysis X
  • Year:
  • 2011

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Abstract

Life science research aims at understanding the relationships in genomics, proteomics and metabolomics on all levels of biological self organization, dealing with data of increasing dimension and complexity. Bioimages represent a new data domain in this context, gaining growing attention since it closes important gaps left by the established molecular techniques. We present a new, web-based strategy that allows a new way of collaborative bioimage interpretaion through knowledge integration. We show, how this can be supported by combining data mining algorithms running on powerful compute servers and a next generation rich internet application (RIA) front-end offering database/project management and high-level tools for exploratory data analysis and annotation. We demonstrate our system BioIMAX using a bioimage dataset from High-Content Screening experiments to study bacterial infection in cell cultures.