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ISAAC - InterSpecies Analysing Application using Containers.

Herbert Baier, Jörg Schultz1

  • 1Department of Bioinformatics, Biocenter, University of Würzburg, Am Hubland, Würzburg 97074, Germany. joerg.schultz@biozentrum.uni-wuerzburg.de.

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|January 17, 2014
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Summary
This summary is machine-generated.

This study introduces ISAAC, an InterSpecies Analysing Application using Containers, for interactive gene set analysis. It enables collaborative exploration of biological data across different viewpoints and species.

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Area of Science:

  • Bioinformatics
  • Computational Biology
  • Genomics

Background:

  • Biological data, including genes, transcripts, and proteins, are fragmented across numerous databases.
  • Existing analysis tools often focus on specific feature enrichments but lack interactive exploration and modification capabilities.
  • Current tools do not facilitate dynamic gene list refinement based on evolving research narratives.

Purpose of the Study:

  • To develop an integrated web-based application for interactive analysis of gene, transcript, and protein sets.
  • To enable users to explore biological data from multiple viewpoints and modify analysis sets dynamically.
  • To facilitate collaborative research through group functionalities and data sharing.

Main Methods:

  • Development of ISAAC (InterSpecies Analysing Application using Containers), a JavaEE-based web tool.
  • Implementation of interactive analysis with history and snapshot features for state tracking and reversion.
  • Integration of multiple biological contexts: genomes, protein functions, interactions, pathways, regulation, diseases, and drugs.
  • Inclusion of orthology-based species translation for gene set comparison.
  • Development of group functionalities for collaborative data and results sharing.

Main Results:

  • ISAAC provides a platform for analyzing sets of genes, transcripts, and proteins under diverse biological perspectives.
  • Users can interactively modify gene sets and revert to previous analysis states.
  • The tool supports cross-species analysis via automatic orthology mapping.
  • Group functionalities allow for seamless data exchange and collaborative analysis within research teams.
  • ISAAC integrates various biological data types, including genomes, protein functions, interactions, pathways, regulation, diseases, and drugs.

Conclusions:

  • ISAAC bridges the gap between primary biological databases and large-scale gene list analysis tools.
  • Its modular design and JavaEE architecture simplify the integration of new analysis modules.
  • An extensive web-based administration interface supports easy installation and third-party data integration.
  • ISAAC is ideally suited for highly explorative, interactive, and collaborative analyses of biological data sets.