Proteomics

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LncReader: identification of dual functional long non-coding RNAs using multi-head self-attention mechanism


ABSTRACT: The dual functional lncRNAs have been intensively studied and identified to be involved in various fundamental cellular processes recently. It is essential to understand in which context when a dual functional lncRNA serves as a non-coding RNA or a template for coding peptide, particularly in some pathological conditions. However, apart from time consuming and cell type specific experiments, there is virtually no in-silico method for predicting the identity of dual functional lncRNAs. Here, we developed a deep-learning model with multi-head self-attention mechanism, LncReader, to identify dual functional lncRNAs based on their sequence, physicochemical and secondary structural features. Our data demonstrated that LncReader showed multiple advantage compared to various classical machine learning methods. Moreover, to obtain independent in-house datasets for robust testing, mass spectrometry proteomics combined with RNA-seq were applied in four leukemia cell lines. Remarkably, LncReader achieved the best performance among all these datasets. Therefore, LncReader provides a sophisticated and practical tool that enables fast dual functional lncRNAs identification.

INSTRUMENT(S): Thermo Fisher Scientific instrument model

ORGANISM(S): Homo Sapiens (human)

TISSUE(S): Leukocyte, Cell Culture

SUBMITTER: Tianyuan Liu  

LAB HEAD: Dong Wang

PROVIDER: PXD030066 | Pride | 2023-04-26

REPOSITORIES: Pride

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Publications

LncReader: identification of dual functional long noncoding RNAs using a multi-head self-attention mechanism.

Liu Tianyuan T   Zou Bohao B   He Manman M   Hu Yongfei Y   Dou Yiying Y   Cui Tianyu T   Tan Puwen P   Li Shaobin S   Rao Shuan S   Huang Yan Y   Liu Sixi S   Cai Kaican K   Wang Dong D  

Briefings in bioinformatics 20230101 1


Long noncoding ribonucleic acids (RNAs; LncRNAs) endowed with both protein-coding and noncoding functions are referred to as 'dual functional lncRNAs'. Recently, dual functional lncRNAs have been intensively studied and identified as involved in various fundamental cellular processes. However, apart from time-consuming and cell-type-specific experiments, there is virtually no in silico method for predicting the identity of dual functional lncRNAs. Here, we developed a deep-learning model with a  ...[more]

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