HuntMi: an efficient and taxon-specific approach in pre-miRNA identification

Adam Gudyś1, Michał Wojciech Szcześniak2, Marek Sikora1 and Izabela Makałowska2, BMC Bioinformatics, 14:83 (click here to see the paper).

1.     Institute of Computer Science, Faculty Of Automatic Control, Electronics And Computer Science, Silesian University of Technology, Gliwice, Poland

2.     Laboratory of Bioinformatics, Faculty of Biology, Adam Mickiewicz University, Poznań, Poland

 

Contact: adam.gudys@polsl.pl, miszcz@amu.edu.pl

 

Cross validation datasets:

       data_sequences.zip sequences used in the research in fasta format.

       data_features_base.zip arff files containing base representation of examined sequences (21 features).

       data_features_extended.zip arff files containing extended representation of examined sequences (21+7 features). This is a default representation for HuntMi software.

 

Comparative datasets:

       animals_miRBase18-19.zip animal sequences newly introduced in miRBase 18-19 used in comparative experiments.

       plants_miRBase18-19.zip - plant sequences newly introduced in miRBase 18-19 used in comparative experiments.

 

Software (please refer to the README file for all the details):

       HuntMi.tar.gz HuntMi package for miRNA classification. Requires Linux machine with Perl 5.10 (see README file when running on earlier Perl versions).

       ROCSelect.jar Weka plugin with ROC-select procedure to be used for training models on custom datasets. Plugin works correctly with 3.6.x version of Weka.

       ROCSelect.model-cfg Weka classifier configuration file with default ROCSelect parameters.

       README readme file with all the instructions for miRNA identification as well as model training.

 

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