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Mammalian Genome

, Volume 21, Issue 1–2, pp 1–12 | Cite as

Computational approaches for microRNA studies: a review

  • Li Li
  • Jianzhen XuEmail author
  • Deyin Yang
  • Xiaorong Tan
  • Hongfei Wang
Article

Abstract

MicroRNAs (miRNAs) are one class of tiny, endogenous RNAs that can regulate messenger RNA (mRNA) expression by targeting homologous sequences in mRNAs. Their aberrant expressions have been observed in many cancers and several miRNAs have been convincingly shown to play important roles in carcinogenesis. Since the discovery of this small regulator, computational methods have been indispensable tools in miRNA gene finding and functional studies. In this review we first briefly outline the biological findings of miRNA genes, such as genomic feature, biogenesis, gene structure, and functional mechanism. We then discuss in detail the three main aspects of miRNA computational studies: miRNA gene finding, miRNA target prediction, and regulation of miRNA genes. Finally, we provide perspectives on some emerging issues, including combinatorial regulation by miRNAs and functional binding sites beyond the 3′-untranslated region (3′UTR) of target mRNAs. Available online resources for miRNA computational studies are also provided.

Keywords

miRNA Target miRNA Gene Target Prediction miRNA Binding Site Viral miRNAs 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Abbreviations

miRNAs

MicroRNAs

pri-miRNAs

Primary miRNAs

UTR

Untranslated region

miRNPs

Micro-ribonucleoproteins

miRISCs

miRNA-induced silencing complexes

AGO

Argonaute

SVM

Support vector machine

HMM

Hidden Markov model

HITS-CLIP

High-throughput sequencing of RNAs isolated by crosslinking immunoprecipitation

TFs

Transcription factors

Pol II or Pol III

RNA polymerase II or III

TSS

Transcription start site

Notes

Acknowledgments

We apologize for the failure to cite many of the important and relevant papers in this field due to space limitations. We thank Dr. Baowei Peng and Ms. Jian Fan for critical reading of the manuscript. This work was partially supported by the National Natural Science Foundation of China (Grant No. 60601010), the Science Foundation of the education department of Henan province (Grant No. 2006210002), and the Award for Outstanding Young Teacher of Tongji University (No.TJYQ08014).

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Copyright information

© Springer Science+Business Media, LLC 2009

Authors and Affiliations

  • Li Li
    • 1
  • Jianzhen Xu
    • 2
    Email author
  • Deyin Yang
    • 3
  • Xiaorong Tan
    • 2
  • Hongfei Wang
    • 4
  1. 1.Department of Medical Genetics, School of MedicineTongji UniversityShanghaiPeople’s Republic of China
  2. 2.College of BioengineeringHenan University of TechnologyZhengzhouPeople’s Republic of China
  3. 3.Medical College of Soochow UniversitySuzhouPeople’s Republic of China
  4. 4.Kaifeng UniversityKaifengPeople’s Republic of China

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