Literature DB >> 24338400

Predicting the target genes of microRNA based on microarray data.

B Cao1, T Ji, B Zhou, J Zou, G Q Jiao.   

Abstract

MicroRNAs (miRNAs) are small non-coding RNAs of approximately 22 nucleotides in length, which play important roles in regulating gene expression post-transcriptionally. Several computational methods and algorithms have been developed to predict miRNA targets. In this study, we described a method that can be used to integrate miRNA target prediction data from multiple sources and gene expression data to predict target genes of particular miRNAs. We used hsa-miR-375 as an example to test the feasibility of our method. A total of 5645 target genes of hsa-miR-375 were identified from five prediction programs, and among them, 2440 target genes were shared by at least 2 of these 5 programs. By using our method, the number was further reduced to 149 and 5 of the 149 target genes had been validated by previous study. This is a simple yet highly effective approach.

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Year:  2013        PMID: 24338400     DOI: 10.4238/2013.December.2.4

Source DB:  PubMed          Journal:  Genet Mol Res        ISSN: 1676-5680


  3 in total

1.  MicroRNA target prediction: theory and practice.

Authors:  Mathias Wagner; Benjamin Vicinus; Vilma Oliveira Frick; Michael Auchtor; Claudia Rubie; Pascal Jeanmonod; Tereza A Richards; Roland Linder; Frank Weichert
Journal:  Mol Genet Genomics       Date:  2014-06-18       Impact factor: 3.291

2.  Detection and comparison of microRNAs in the caprine mammary gland tissues of colostrum and common milk stages.

Authors:  Jinxing Hou; Xiaopeng An; Yuxuan Song; Binyun Cao; Heping Yang; Zhou Zhang; Wenzheng Shen; Yunpu Li
Journal:  BMC Genet       Date:  2017-05-02       Impact factor: 2.797

3.  MicroRNA-550a is associated with muscle system conferring poorer survival for esophageal cancer.

Authors:  Housong Hong; Taisheng Liu; Huazhen Wu; Jinye Zhang; Xiaoshun Shi; Xiaobing Le; Allen M Chen; Haiyun Mo; Qianqian Huang; Huaping Zhou; Xuguang Rao
Journal:  Biosci Rep       Date:  2019-05-31       Impact factor: 3.840

  3 in total

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