SGCL-LncLoc: An Interpretable Deep Learning Model for Improving lncRNA Subcellular Localization Prediction with Supervised Graph Contrastive Learning

SGCL-LncLoc: An Interpretable Deep Learning Model for Improving lncRNA Subcellular Localization Prediction with Supervised Graph Contrastive Learning

Understanding the subcellular localization of long non-coding RNAs (lncRNAs) is crucial for unraveling their functional mechanisms. While previous computational methods have made progress in predicting lncRNA subcellular localization, most of them ignore the sequence order information by relying on...

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Bibliographic Details
Main Authors: Min Li, Baoying Zhao, Yiming Li, Pingjian Ding, Rui Yin, Shichao Kan, Min Zeng
Format: Article
Language:English
Published: Tsinghua University Press 2024-09-01
Series:Big Data Mining and Analytics
Subjects:
supervised contrastive learning
long non-coding rna (lncrna)
subcellular localization prediction
deep learning
graph convolutional network (gcn)
Online Access:https://www.sciopen.com/article/10.26599/BDMA.2024.9020002
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https://www.sciopen.com/article/10.26599/BDMA.2024.9020002

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