Discovery of Relationships Between Long Non-Coding RNAs and Genes in Human Diseases Based on Tensor Completion

• Main Authors: Chen Peng, Liang Zou, De-Shuang Huang
• Format: Article
• Language: English
• Published: IEEE 2018-01-01
• Series: IEEE Access
• Subjects: Diseases; lncRNAs; tensor; cancers; genes
• Online Access: https://ieeexplore.ieee.org/document/8478258/

Thousands of long non-coding RNAs (lncRNAs) are encoded by mammalian genomes and play important roles in various biological processes, including the regulation of gene transcription. Through these relationships, lncRNAs can participate in proliferation, differentiation, and cytoprotective programs, which implies their critical roles in human diseases, especially cancers. Therefore, there is an urgent need to study the relationships between lncRNAs and genes in human diseases, which will help uncover the mechanisms underlying disease progression. In this paper, we explore the relationships between lncRNAs and genes in various diseases through a tensor completion-based approach (TCA). The results of performance evaluation suggest that TCA can obtain a significantly better performance than the baseline method. Moreover, top ranked relationships with highest average scores in all diseases corroborate the effectiveness of TCA and the reliability of the predicted results. Case study of hepatocellular carcinoma (HCC) indicates that the elements of the top ranked relationships may be functionally implicated in HCC. Furthermore, three lncRNAs (HULC, MALAT1, and BANCR) and gene HOXB7 are found to be important in HCC, which are consistent with the newest reports and existing literatures.