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Related Experiment Videos

From transcriptomics to bibliomics.

Bertrand H Rihn1, Solveig Vidal, Claude Nemurat

  • 1Institut National de Recherche et de S curit (INRS), Vandoeuvre-les-Nancy, France. Bertrand.Rihn@pharmaca.uhp-nancy.fr

Medical Science Monitor : International Medical Journal of Experimental and Clinical Research
|August 28, 2003
PubMed
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We developed the Documentation and Information LIBrary (DILIB) tool to link gene expression data with literature. This bibliomics approach helps discover new gene functions and research areas from vast biological datasets.

Area of Science:

  • Bioinformatics
  • Genomics
  • Molecular Biology

Background:

  • Modern biological research focuses on large-scale genomic data, moving beyond single genes.
  • Analyzing vast amounts of transcriptomic and proteomic data presents challenges in linking findings to structured bibliographical information.
  • Retrieving rare, highly structured information from complex biological datasets remains a significant hurdle.

Purpose of the Study:

  • To develop a tool for retrieving, organizing, and analyzing large-scale biological data from the internet.
  • To link differentially expressed genes with relevant scientific literature and databases.
  • To facilitate the discovery of new gene functions and research avenues through integrated data analysis.

Main Methods:

  • Development of the Documentation and Information LIBrary (DILIB) tool.

Related Experiment Videos

  • Utilizing gene identifiers (Single Identifier, GenBank accession number) to link gene expression data with Medline records.
  • Automated retrieval, analysis, and comparison of thousands of descriptors related to gene clusters.

    • Main Results:

    • Successfully associated literature with expressed genes and linked functional transcriptomes across experiments.
    • Enabled the association of specific descriptors with experimental data, aiding in the definition of new research areas.
    • Demonstrated the ability to identify potential new functions for co-expressed genes, as exemplified by analysis of 'integrin', 'interleukin', and 'CD Antigens' in mesotheliomas.

    Conclusions:

    • Introduction of 'bibliomics' as a novel concept for extracting high-quality, rare information from '-omic' data.
    • Bibliomics leverages systematic literature searching to organize and analyze gene-related information from existing databases.
    • This approach supports the discovery of functional relationships among co-expressed genes within '-omic' sciences.