GCNFORMER: graph convolutional network and transformer for predicting lncRNA-disease associations

GCNFORMER: graph convolutional network and transformer for predicting lncRNA-disease associations

Abstract Background A growing body of researches indicate that the disrupted expression of long non-coding RNA (lncRNA) is linked to a range of human disorders. Therefore, the effective prediction of lncRNA-disease association (LDA) can not only suggest solutions to diagnose a condition but also sav...

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Bibliographic Details
Main Authors: Dengju Yao, Bailin Li, Xiaojuan Zhan, Xiaorong Zhan, Liyang Yu
Format: Article
Language:English
Published: BMC 2024-01-01
Series:BMC Bioinformatics
Subjects:
LncRNA-disease association prediction
Graph convolutional network
transformer
Machine learning
Multiheaded attention mechanism
Online Access:https://doi.org/10.1186/s12859-023-05625-1

Internet

https://doi.org/10.1186/s12859-023-05625-1

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