Literature DB >> 17720479

Computational methods for microRNA target prediction.

Yuka Watanabe1, Masaru Tomita, Akio Kanai.   

Abstract

The discovery of microRNAs (miRNAs) has introduced a new paradigm into gene regulatory systems. Large numbers of miRNAs have been identified in a wide range of species, and most of them are known to downregulate translation of messenger RNAs (mRNAs) via imperfect binding of the miRNA to a specific site or sites in the 3' untranslated region (UTR) of the mRNA. Identification of genes targeted by miRNAs is widely believed to be an important step toward understanding the role of miRNAs in gene regulatory networks. As part of the effort to understand interactions between miRNAs and their targets, computational algorithms have been developed based on observed rules for features such as the degree of hybridization between the two RNA molecules. These in silico approaches provide important tools for miRNA target detection, and together with experimental validation, help to reveal regulated targets of miRNAs. Here, we summarize the knowledge that has been accumulated about the principles of target recognition by miRNAs and the currently available computational methodologies for prediction of miRNA target genes.

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Year:  2007        PMID: 17720479     DOI: 10.1016/S0076-6879(07)27004-1

Source DB:  PubMed          Journal:  Methods Enzymol        ISSN: 0076-6879            Impact factor:   1.600


  46 in total

1.  Computational methods for the identification of microRNA targets.

Authors:  Yang Dai; Xiaofeng Zhou
Journal:  Open Access Bioinformatics       Date:  2010-05-01

Review 2.  A study of miRNAs targets prediction and experimental validation.

Authors:  Yong Huang; Quan Zou; Haitai Song; Fei Song; Ligang Wang; Guozheng Zhang; Xingjia Shen
Journal:  Protein Cell       Date:  2010-12-10       Impact factor: 14.870

3.  AccessFold: predicting RNA-RNA interactions with consideration for competing self-structure.

Authors:  Laura DiChiacchio; Michael F Sloma; David H Mathews
Journal:  Bioinformatics       Date:  2015-11-20       Impact factor: 6.937

Review 4.  Got target? Computational methods for microRNA target prediction and their extension.

Authors:  Hyeyoung Min; Sungroh Yoon
Journal:  Exp Mol Med       Date:  2010-04-30       Impact factor: 8.718

Review 5.  Modulation of immune responses following solid organ transplantation by microRNA.

Authors:  Nayan J Sarma; Venkataswarup Tiriveedhi; Sabarinathan Ramachandran; Jeffrey Crippin; William Chapman; T Mohanakumar
Journal:  Exp Mol Pathol       Date:  2012-10-01       Impact factor: 3.362

6.  Hodgkin lymphoma cell lines are characterized by a specific miRNA expression profile.

Authors:  Johan H Gibcus; Lu Ping Tan; Geert Harms; Rikst Nynke Schakel; Debora de Jong; Tjasso Blokzijl; Peter Möller; Sibrand Poppema; Bart-Jan Kroesen; Anke van den Berg
Journal:  Neoplasia       Date:  2009-02       Impact factor: 5.715

7.  Frequent amplification of a chr19q13.41 microRNA polycistron in aggressive primitive neuroectodermal brain tumors.

Authors:  Meihua Li; Kyle F Lee; Yuntao Lu; Ian Clarke; David Shih; Charles Eberhart; V Peter Collins; Tim Van Meter; Daniel Picard; Limei Zhou; Paul C Boutros; Piergiorgio Modena; Muh-Lii Liang; Steve W Scherer; Eric Bouffet; James T Rutka; Scott L Pomeroy; Ching C Lau; Michael D Taylor; Amar Gajjar; Peter B Dirks; Cynthia E Hawkins; Annie Huang
Journal:  Cancer Cell       Date:  2009-12-08       Impact factor: 31.743

8.  Specificity and functionality of microRNA inhibitors.

Authors:  Barbara Robertson; Andrew B Dalby; Jon Karpilow; Anastasia Khvorova; Devin Leake; Annaleen Vermeulen
Journal:  Silence       Date:  2010-04-01

9.  MicroRNA: Implications for Alzheimer Disease and other Human CNS Disorders.

Authors:  Olivier C Maes; Howard M Chertkow; Eugenia Wang; Hyman M Schipper
Journal:  Curr Genomics       Date:  2009-05       Impact factor: 2.236

10.  Modeling post-transcriptional regulation activity of small non-coding RNAs in Escherichia coli.

Authors:  Rui-Sheng Wang; Guangxu Jin; Xiang-Sun Zhang; Luonan Chen
Journal:  BMC Bioinformatics       Date:  2009-04-29       Impact factor: 3.169

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