Accurate prediction of protein-lncRNA interactions by diffusion and HeteSim features across heterogeneous network
Abstract Background Identifying the interactions between proteins and long non-coding RNAs (lncRNAs) is of great importance to decipher the functional mechanisms of lncRNAs. However, current experimental techniques for detection of lncRNA-protein interactions are limited and inefficient. Many method...
Main Authors: | Lei Deng, Junqiang Wang, Yun Xiao, Zixiang Wang, Hui Liu |
---|---|
Format: | Article |
Language: | English |
Published: |
BMC
2018-10-01
|
Series: | BMC Bioinformatics |
Subjects: | |
Online Access: | http://link.springer.com/article/10.1186/s12859-018-2390-0 |
Similar Items
-
GBDTL2E: Predicting lncRNA-EF Associations Using Diffusion and HeteSim Features Based on a Heterogeneous Network
by: Jiaqi Wang, et al.
Published: (2020-04-01) -
Predicting miRNA-disease associations using a hybrid feature representation in the heterogeneous network
by: Minghui Liu, et al.
Published: (2020-10-01) -
Prediction of lncRNA-protein interactions using HeteSim scores based on heterogeneous networks
by: Yun Xiao, et al.
Published: (2017-06-01) -
A Hybrid Prediction Method for Plant lncRNA-Protein Interaction
by: Jael Sanyanda Wekesa, et al.
Published: (2019-05-01) -
LPI-deepGBDT: a multiple-layer deep framework based on gradient boosting decision trees for lncRNA–protein interaction identification
by: Liqian Zhou, et al.
Published: (2021-10-01)