ncRNAInter

NOTE: the scripts of feature generation for comprehensive RNA representation have been updated

ncRNAInter: A Novel Strategy Based on Graph Neural Network to Discover Interactions between lncRNA and miRNA

Hanyu Zhang, Yunxia Wang, Ziqi Pan, Xiuna Sun, Minjie Mou, Bing Zhang, Zhanrong Li, Honglin Li* and Feng Zhu*

Install

1. Download pretrained models and source codes of ncRNAInter.
2. ncRNAInter should be deployed on Linux.
3. The ncRNAInter tree includes three package:

 |- comparison
     |- Human
     	|- CNN
     	|- LMI-INGI
     	|- LncMirNet
     	|- PmliPred_human
     	|- preMLI_human
     	|- RF
     	|- SVM
     |- Plants
        |- ncRNAInter_plant
        |- PmliPred_plant
     |- Virus
     	|- ncRNAInter_virus
 |- main
     |- data
     |- data_process
     |- feature_importance
     |- models
     |- pretrained
     |- run_result
     |- utils
     |- K_fold_trainval.py
     |- run.py
 |- statistic
    |- figure_*.py
 |- requirements.txt
 |- README.md
 |- LICENSE

Directory of comparison deposits the reproduced methods used in comparison with ncRNAInter, including their datasets and retrained models.

Directory of statistic deposits the scripts we used to plot.

Directory of main deposits the basis of ncRNAInter, including source code, datasets and pretrained models. Usage of ncRNAInter is explained in ./main/README.md.

Citation and Disclaimer

For more information, please refer to and cite: Zhang, Hanyu et al. ncRNAInter: a novel strategy based on graph neural network to discover interactions between lncRNA and miRNA. Briefings in bioinformatics, bbac411. 4 Oct. 2022. PMID:36198065. https://doi.org/10.1093/bib/bbac411.

Should you have any questions, please contact Dr. Zhang at hanyu_zhang@zju.edu.cn