iLoc-miRNA: extracellular/intracellular miRNA prediction using deep BiLSTM with attention mechanism

Author:

Zhang Zhao-Yue1,Ning Lin2,Ye Xiucai3ORCID,Yang Yu-He4,Futamura Yasunori13,Sakurai Tetsuya13,Lin Hao4ORCID

Affiliation:

1. Tsukuba Life Science Innovation Program, University of Tsukuba , Tsukuba 3058577, Japan

2. School of Healthcare Technology, Chengdu Neusoft University , 611844, Chengdu, China

3. Department of Computer Science, University of Tsukuba , Tsukuba 3058577, Japan

4. Center for Information Biology, University of Electronic Science and Technology of China , Chengdu 610054, China

Abstract

Abstract The location of microRNAs (miRNAs) in cells determines their function in regulation activity. Studies have shown that miRNAs are stable in the extracellular environment that mediates cell-to-cell communication and are located in the intracellular region that responds to cellular stress and environmental stimuli. Though in situ detection techniques of miRNAs have made great contributions to the study of the localization and distribution of miRNAs, miRNA subcellular localization and their role are still in progress. Recently, some machine learning-based algorithms have been designed for miRNA subcellular location prediction, but their performance is still far from satisfactory. Here, we present a new data partitioning strategy that categorizes functionally similar locations for the precise and instructive prediction of miRNA subcellular location in Homo sapiens. To characterize the localization signals, we adopted one-hot encoding with post padding to represent the whole miRNA sequences, and proposed a deep bidirectional long short-term memory with the multi-head self-attention algorithm to model. The algorithm showed high selectivity in distinguishing extracellular miRNAs from intracellular miRNAs. Moreover, a series of motif analyses were performed to explore the mechanism of miRNA subcellular localization. To improve the convenience of the model, a user-friendly web server named iLoc-miRNA was established (http://iLoc-miRNA.lin-group.cn/).

Funder

National Natural Science Foundation of China

Japan Society for the Promotion of Science

Japan Science and Technology Corporation

Publisher

Oxford University Press (OUP)

Subject

Molecular Biology,Information Systems

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