GM-lncLoc: LncRNAs subcellular localization prediction based on graph neural network with meta-learning

BMC Genomics

Research

Lin Tang¹  Ting Wang²  Xi Deng²  Junzhe Cai²  Lin Liu² 

[1] Key Laboratory of Educational Information for Nationalities Ministry of Education, Yunnan Normal University, Kunming, Yunnan, China;School of Information, Yunnan Normal University, Kunming, Yunnan, China;

关键词: lncRNA;    Subcellular localization;    Graph neural network;    Meta-learning;    Classification;   

DOI  :  10.1186/s12864-022-09034-1

 received in 2022-06-29, accepted in 2022-11-21,  发布年份 2022

来源: Springer

【 摘 要 】

In recent years, a large number of studies have shown that the subcellular localization of long non-coding RNAs (lncRNAs) can bring crucial information to the recognition of lncRNAs function. Therefore, it is of great significance to establish a computational method to accurately predict the subcellular localization of lncRNA. Previous prediction models are based on low-level sequences information and are troubled by the few samples problem. In this study, we propose a new prediction model, GM-lncLoc, which is based on the initial information extracted from the lncRNA sequence, and also combines the graph structure information to extract high level features of lncRNA. In addition, the training mode of meta-learning is introduced to obtain meta-parameters by training a series of tasks. With the meta-parameters, the final parameters of other similar tasks can be learned quickly, so as to solve the problem of few samples in lncRNA subcellular localization. Compared with the previous methods, GM-lncLoc achieved the best results with an accuracy of 93.4 and 94.2% in the benchmark datasets of 5 and 4 subcellular compartments, respectively. Furthermore, the prediction performance of GM-lncLoc was also better on the independent dataset. It shows the effectiveness and great potential of our proposed method for lncRNA subcellular localization prediction. The datasets and source code are freely available at https://github.com/JunzheCai/GM-lncLoc.

【 授权许可】

CC BY   
© The Author(s) 2022

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