JinmiaoS / RPITER

A hierarchical deep learning framework for ncRNA-protein interaction prediction.

RPITER

A hierarchical deep learning model for predicting ncRNA-protein interaction.

The sample, data and result directories contain model codes, tested data sets and generated results, respectively. The depended python packages are listed in requirements.txt. The package versions should be followed by users in their environments to achieve the supposed performance.

How to run

The program is in Python 3.6 using Keras and Tensorflow backends. Use the below bash command to run RPITER.

    python rpiter.py -d dataset

The parameter of dataset could be RPI369, RPI488, RPI1807, RPI2241 or NPInter. Then, RPITER will perform 5-fold cross validation on the specific dataset.

Five RPI datasets

The widely used RPI benchmark datasets are organized in the data directory.

Dataset	#Positive pairs	#Negative pairs	RNAs	Proteins	Reference
RPI369	369	0	332	338	[1]
RPI488	243	245	25	247	[2]
RPI1807	1807	1436	1078	3131	[3]
RPI2241	2241	0	841	2042	[1]
NPInter	10412	0	4636	449	[4]

Help

For any questions, feel free to contact me by [e-mail] or start an issue instead.

[1] Muppirala, U.K.; Honavar, V.G.; Dobbs, D. Predicting RNA-Protein Interactions Using Only Sequence Information. Bmc Bioinformatics 2011, 12. doi:Artn 489 10.1186/1471-2105-12-489.

[2] Pan, X.Y.; Fan, Y.X.; Yan, J.C.; Shen, H.B. IPMiner: hidden ncRNA-protein interaction sequential pattern mining with stacked autoencoder for accurate computational prediction. Bmc Genomics 2016, 17. doi:ARTN 582 10.1186/s12864-016-2931-8.

[3] Suresh, V.; Liu, L.; Adjeroh, D.; Zhou, X.B. RPI-Pred: predicting ncRNA-protein interaction using sequence and structural information. Nucleic Acids Research 2015, 43, 1370–1379. doi:10.1093/nar/gkv020.

[4] Yuan, J.;Wu,W.; Xie, C.Y.; Zhao, G.G.; Zhao, Y.; Chen, R.S. NPInter v2.0: an updated database of ncRNA interactions. Nucleic Acids Research 2014, 42, D104–D108. doi:10.1093/nar/gkt1057.