Title:LPLSG: Prediction of lncRNA-protein Interaction Based on Local
Network Structure
Volume: 18
Issue: 3
Author(s): Wei Wang*, Yongqing Wang, Bin Sun, Shihao Liang, Dong Liu, Hongjun Zhang and Xianfang Wang
Affiliation:
- College of Computer and Information Engineering, Henan Normal University, Xinxiang, 453007, China
- Key Laboratory
of Artificial Intelligence and Personalized Learning in Education of Henan Province, Xinxiang, 453007, China
- Big Data Engineering Laboratory for Teaching Resources and assessment of Education Quality of Henan Province,
Xinxiang, 453007, China
Keywords:
lncRNA-protein interactions, binary network, local structure, similar node, similar computer, scores network.
Abstract:
Background: The interaction between RNA and protein plays an important role in life activities.
Long ncRNAs (lncRNAs) are large non-coding RNAs, and have received extensive attention in recent
years. Because the interaction between RNA and protein is tissue-specific and condition-specific, it
is time-consuming and expensive to predict the interaction between lncRNA and protein based on biological
wet experiments.
Objective: The contribution of this paper is to propose a method for prediction based on the local structural
similarity of lncRNA-protein interaction (LPI) network.
Methods: The method computes the local structure similarity of network space, and maps it to LPI
space, and uses an innovative algorithm that combined Resource Allocation and improved Collaborative
Filtering algorithm to calculate the potential LPI.
Conclusion: AUPR and AUC are significantly better than the five popular baseline methods. In addition,
the case study shows that some results of LPLSG prediction on the actual data set have been verified
by NPInterV4.0 database and some literatures.