AUTHOR=Wei Meng-Meng , Yu Chang-Qing , Li Li-Ping , You Zhu-Hong , Ren Zhong-Hao , Guan Yong-Jian , Wang Xin-Fei , Li Yue-Chao TITLE=LPIH2V: LncRNA-protein interactions prediction using HIN2Vec based on heterogeneous networks model JOURNAL=Frontiers in Genetics VOLUME=14 YEAR=2023 URL=https://www.frontiersin.org/journals/genetics/articles/10.3389/fgene.2023.1122909 DOI=10.3389/fgene.2023.1122909 ISSN=1664-8021 ABSTRACT=

LncRNA-protein interaction plays an important role in the development and treatment of many human diseases. As the experimental approaches to determine lncRNA–protein interactions are expensive and time-consuming, considering that there are few calculation methods, therefore, it is urgent to develop efficient and accurate methods to predict lncRNA-protein interactions. In this work, a model for heterogeneous network embedding based on meta-path, namely LPIH2V, is proposed. The heterogeneous network is composed of lncRNA similarity networks, protein similarity networks, and known lncRNA-protein interaction networks. The behavioral features are extracted in a heterogeneous network using the HIN2Vec method of network embedding. The results showed that LPIH2V obtains an AUC of 0.97 and ACC of 0.95 in the 5-fold cross-validation test. The model successfully showed superiority and good generalization ability. Compared to other models, LPIH2V not only extracts attribute characteristics by similarity, but also acquires behavior properties by meta-path wandering in heterogeneous networks. LPIH2V would be beneficial in forecasting interactions between lncRNA and protein.