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Predicting Functional MicroRNA-mRNA Interactions

  • Zixing Wang
  • Yin LiuEmail author
Protocol
Part of the Methods in Molecular Biology book series (MIMB, volume 1580)

Abstract

MicroRNAs (miRNAs) are small RNA molecules that play key regulatory roles in general biological processes and disease pathogenesis. These small RNA molecules interact with their target mRNAs to induce mRNA degradation and/or inhibit the translation of mRNAs into proteins. Therefore, identifying miRNA targets is an essential step to fully understand the regulatory effects of miRNAs. Here, we describe a regularized regression approach that integrates the sequence information with the miRNA and mRNA expression profiles for detecting miRNA targets. This method takes into account the full spectrum of gene sequence features of miRNA targets, including the thermodynamic stability, the accessibility energy, and the context features of the target sites,. Given these sequence features for each putative miRNA-mRNA interaction and their expression values, this model is able to quantify the down-regulation effect of each miRNA on its targets while simultaneously estimating the contribution of each sequence feature for predicting functional miRNA-mRNA interactions.

Key words

MiRNA target identification miRNA and mRNA expression profiles Regularized regression Sequence features Context score Thermodynamic stability 

Notes

Acknowledgment

This work is supported in part by NIH grant R01 LM010022 and the seed grant from the University of Texas Health Science Center at Houston.

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Copyright information

© Springer Science+Business Media LLC 2017

Authors and Affiliations

  1. 1.University of Texas M.D. Anderson Cancer Center77455 Fannin Street, HoustonUSA
  2. 2.Department of Neurobiology and AnatomyUniversity of Texas Health Science Center at HoustonHoustonUSA
  3. 3.University of Texas Graduate School of Biomedical ScienceHoustonUSA

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