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Related Experiment Videos

CoGenT++: an extensive and extensible data environment for computational genomics.

Leon Goldovsky1, Paul Janssen, Dag Ahrén

  • 1Computational Genomics Group, The European Bioinformatics Institute EMBL, Cambridge Outstation, Cambridge CB10 1SD, UK.

Bioinformatics (Oxford, England)
|October 12, 2005
PubMed
Summary
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CoGenT++ offers a robust computational environment for comparative genomics, enhancing data consistency and accessibility. This platform supports large-scale analyses and manual browsing of genomic data.

Area of Science:

  • Genomics
  • Bioinformatics
  • Computational Biology

Background:

  • CoGenT++ addresses critical challenges in computational genomics research, including data consistency, reproducibility, scalability, and accessibility.
  • Existing data environments often lack comprehensive integration and efficient data handling for large-scale genomic studies.

Purpose of the Study:

  • To introduce CoGenT++ as a unified data environment for comparative and functional genomics.
  • To describe the scalable implementation of ProXSim and derived databases for advanced genomic analyses.

Main Methods:

  • CoGenT++ redistributes fully sequenced genomes, storing species, gene names, and protein sequences.
  • A scalable ProXSim implementation creates an all-against-all similarity database for pairwise genome sequence relationships.

Related Experiment Videos

  • Derived databases (AllFuse, OFAM, TRIBES, ProfUse) are generated for gene fusions, orthologs, protein families, and phylogenetic profiles.
  • Main Results:

    • CoGenT++ provides a scalable and accessible platform for computational genomics.
    • The ProXSim database enables efficient storage and retrieval of pairwise genome similarities.
    • Derived databases facilitate various downstream analyses, including disease gene prediction and phylogenetic reconstruction.

    Conclusions:

    • CoGenT++ offers a comprehensive computational environment for genomics.
    • The platform supports both large-scale automated analyses and manual data exploration.
    • CoGenT++ enhances the accessibility and utility of genomic data for research.