miRBind

miRBind is a machine learning method based on ResNet. It learns the rules of miRNA:target binding and provides a probability for the potential binding of a pair of given miRNA and target sequence.

Have a look at our paper miRBind: A Deep Learning Method for miRNA Binding Classification for more information about our work.

Web application

The user-friendly miRBind web application for performing predictions https://ml-bioinfo-ceitec.github.io/miRBind/

Installation

Using Git:

git clone https://github.com/ML-Bioinfo-CEITEC/miRBind.git

git clone git@gitlab.com:RBP_Bioinformatics/miRBind.git

Prerequisites

mRBind is implemented in python using Keras and Tensorflow backend.

Required:

• python, recommended version 3.7
  • Keras 2.7.0
  • tensorflow 2.7.0
  • pandas
  • numpy

Installing

#create a virtual environment:

python -m venv venv

#activate it and install the necessary libraries.

source venv/bin/activate
pip install -r requirements.txt

Prediction

Required input is a tsv file with multiple potential miRNA - target pairs consisting of first column containing miRNA sequence (20 bp long) and second column containing target sequence (50 bp long). To run the model:

cd path/to/miRBind/directory
chmod +x mirbind.py
#if you are not actively sourcing from the previously created virtualenv:
source venv/bin/activate
#run the prediction
./mirbind.py --input <input_file> --output <output_file>

Contact information

CEITEC MU, RBP Bioinformatics - Panagiotis Alexiou, https://www.ceitec.eu/rbp-bioinformatics-panagiotis-alexiou/rg281