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Sfold Tools for MicroRNA Target Prediction.

William Rennie1, Shaveta Kanoria1, Chaochun Liu1

  • 1New York State Department of Health, Wadsworth Center, Center for Medical Science, Albany, NY, USA.

Methods in Molecular Biology (Clifton, N.J.)
|April 10, 2019
PubMed
Summary
This summary is machine-generated.

STarMir and STarMirDB predict microRNA (miRNA) binding sites on messenger RNAs (mRNAs). These tools offer detailed features and a new score for combined regulatory effects, aiding miRNA function research.

Keywords:
CLIPDatabaseEfficacyQuantitative scoreRNA secondary structureTarget mRNAmiRNAmiRNA binding site

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Area of Science:

  • Computational Biology
  • Bioinformatics
  • Molecular Biology

Background:

  • MicroRNAs (miRNAs) regulate gene expression by binding to target messenger RNAs (mRNAs).
  • Accurate prediction of miRNA binding sites is crucial for understanding miRNA functions and experimental validation.
  • Existing prediction tools may not fully capture the complexity of miRNA-target interactions.

Purpose of the Study:

  • To introduce STarMir and STarMirDB, advanced computational tools for predicting miRNA binding sites.
  • To provide users with a comprehensive resource for analyzing miRNA-mRNA interactions.
  • To develop a novel scoring system for assessing combined regulatory effects of multiple miRNA binding sites.

Main Methods:

  • Development of STarMir, a web server for user-submitted sequence predictions.
  • Creation of STarMirDB, a database of precomputed transcriptome-wide miRNA binding site predictions.
  • Integration of sequence, thermodynamic, and target structure features, along with logistic probability for confidence assessment.

Main Results:

  • STarMir and STarMirDB offer detailed predictions including confidence scores and graphical representations of miRNA-target hybrids.
  • A new quantitative score is introduced to evaluate the cumulative regulatory impact of multiple seed and seedless binding sites.
  • Both tools are accessible via the Sfold Web application server.

Conclusions:

  • STarMir and STarMirDB enhance the computational prediction of miRNA binding sites.
  • The new quantitative score provides a more holistic view of miRNA-mediated gene regulation.
  • These freely available resources facilitate experimental investigation of miRNA functions.