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Related Experiment Videos

In silico prediction of lncRNA function using tissue specific and evolutionary conserved expression.

Umberto Perron1, Paolo Provero1,2, Ivan Molineris3

  • 1Department of Molecular Biotechnology and Health Sciences, University of Turin, via Nizza 52, Torino, 10126, Italy.

BMC Bioinformatics
|April 1, 2017
PubMed
Summary

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Computational methods can predict long non coding RNA (lncRNA) functions by analyzing gene expression patterns. This approach leverages coexpression data to infer functions for thousands of lncRNAs and proteins, aiding disease research.

Area of Science:

  • Genomics
  • Bioinformatics
  • Molecular Biology

Background:

  • Long non-coding RNAs (lncRNAs) are increasingly recognized for their regulatory roles.
  • Despite growing interest, the functions of most lncRNA genes remain unknown.
  • Computational prediction of lncRNA function is crucial due to limited annotation.

Purpose of the Study:

  • To develop and apply computational methods for predicting the functions of lncRNAs.
  • To infer functional annotations for lncRNAs by leveraging existing protein-coding gene data.
  • To identify potential roles of lncRNAs in biological processes, disease, and cancer.

Main Methods:

  • Utilized the guilt-by-association principle by projecting protein functional information onto lncRNAs based on expression profiles.
Keywords:
CoexpressionDisease gene predictionFunctional predictionlncRNA

Related Experiment Videos

  • Computed gene coexpression networks across 30 human tissues and 9 vertebrate species.
  • Employed a rank product-inspired algorithm to mine coexpression networks for functional predictions.

    • Main Results:

    • Successfully predicted putative new annotations for thousands of lncRNAs and proteins.
    • Identified potential functions including cellular localization and involvement in disease and cancer.
    • Demonstrated the utility of cross-species and tissue-specific expression data for functional inference.

    Conclusions:

    • Tissue-specific coexpression and cross-species gene expression analysis are effective for predicting novel functions of coding genes and lncRNAs.
    • The generated data and prediction tools are accessible via a web interface (www.funcpred.com).