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   Prediction of Human miRNA-Mediated Gene Silencing: mRNA degradation or translational repression
ABOUT microDoR HUMAN:


    microDoR Human (Prediction of Human miRNA-Mediated Gene Silencing:mRNA degradation or translational repression) is an online machine learning algorithm based on SVM (support vector machine) to predict Human miRNA-mediated gene silencing: mRNA degradation or translational repression, and it can also determine whether a mRNA is a target of a miRNA according to Pictar and PITA. The SVM is trained with validated miRNA-target mRNA pairs of mRNA degradation and translational repression, obtained from Tarbase and miRecords databases, and published literatures. A set of 29 features was extracted from the training data and used to train the classifier.
 >View All Targets of a miRNA:
 miRNA(All miRNAs):
(Note:may take some time!)
 >View All miRNAs Targeting an mRNA:
 mRNA(All mRNAs):
(Note:may take some time!)
  >Predict the type of miRNA-mediated Gene Silencing:
  miRNA :
  mRNA:
(Note:may take some time!)

GUIDE INFORMATION FOR microDoR HUMAN:
    The entries in microDoR Human are mainly classified into three categories:
    >View All Targets of a miRNA:
    After selecting one miRNA as input, all targets predicted by PicTar for this miRNA will be shown.
    >View All miRNAs Targeting an mRNA:
    After selecting one mRNA as input, all miRNAs predicted to target this mRNA by PicTar will be shown. (Note: the input must be RefSeq identifiers, e.g.NM_015094.)
    >Predict the type of miRNA-mediated Gene Silencing:
    Selecting a miRNA, and then its target mRNA(must be RefSeq identifiers) is input, the regulation mode , mRNA degradation or translational repression, will be shown if this miRNA-mRNA pair has been identified both by PicTar and PITA. (However we will also note you if the mRNA is not a target of the miRNA according to Pictar and PITA.)

SUPPLEMENTARY DATA:
    LIBSVM is available from http://www.csie.ntu.edu.tw/~cjlin/libsvm/oldfiles/, and version 2.88 is used in our work.
    Supplementary file contains the details of features and all datasets.

AUTHOR:

Xiaofeng Song1; Lei Cheng1; Tao Zhou2; Xuejiang Guo2*;Xiaobai Zhang1;Yi-ping Phoebe Chen4;Ping Han3,*; Jiahao Sha2
    1Department of Biomedical Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016 China;
    2State Key Laboratory of Reproductive Medicine, Department of Histology and Embryology, Nanjing Medical University, Nanjing 210029, China;
    3The First Hospital affiliated to Nanjing Medical University, Nanjing 210029 China;
    4Department of Computer Science and Computer Engineering, La Trobe University, Victoria 3086, Melbourne, Australia;
    *Please cite: Song X, Cheng L, Zhou T, Guo X, Zhang X, Chen YP, Han P, Sha J. Predicting miRNA-mediated gene silencing mode based on miRNA-target duplex features. Comput Biol Med. 2012 Jan;42(1):1-7.

SOME BIOINFORMATICS TOOLS USED IN OUR WORK:


    PicTar(Lall et al2006):PicTar is a computational miRNA target prediction tool based on Hidden Markov Model (HMM) maximum-likelihood to identify common targets of microRNAs. Based on statistical tests and genome-wide alignments of eight vertebrate genomes, PicTar is able to specifically recover published microRNA targets, and experiments suggest that PicTar has an excellent success rate in predicting targets for single microRNAs and for combinations of microRNAs.
    PITA: PITA also is a computational miRNA target prediction tool. It predicts miRNA targets based on hybridization energy and site accessibility.
    RNAhybrid: RNAhybrid is a tool for finding the minimum free energy hybridisation of two sequences.
    RNAfold: RNAfold is a tool to predict secondary structures of single stranded RNA or DNA sequences.
    ARED:ARED is database of AU-rich element-containing mRNAs.


Links(in random order):
pictar    miRBase    RNAhybrid    Entrez Nucleotide     ARED    PITA    LIBSVM


Contact: guo_xuejiang@njmu.edu.cn, hanping200701@163.com
Last updated:2011-09-24
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