MOSDNET: A multi-omics classification framework using simplified multi-view deep discriminant representation learning and dynamic edge GCN with multi-task learning-Reference-Cited by-同舟云学术

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MOSDNET: A multi-omics classification framework using simplified multi-view deep discriminant representation learning and dynamic edge GCN with multi-task learning

Published:2024-10 Issue: Volume:181 Page:109040
ISSN:0010-4825
Container-title:Computers in Biology and Medicine
language:en
Short-container-title:Computers in Biology and Medicine

Author:

Li Min^ORCID,Chen Zihao,Deng Shaobo,Wang Lei,Yu Xiang

Funder

Education Department of Jiangxi Province

National Aerospace Science Foundation of China

National Natural Science Foundation of China National Outstanding Youth Science Fund Project

Publisher

Elsevier BV

Reference59 articles.

1. A computational pipeline for the development of multi-marker bio-signature panels and ensemble classifiers;Günther;BMC Bioinf.,2012

2. SALMON: survival analysis learning with multi-omics neural networks on breast cancer;Huang;Front. Genet.,2019

3. ATHENA: identifying interactions between different levels of genomic data associated with cancer clinical outcomes using grammatical evolution neural network;Kim;BioData Min.,2013

4. DIABLO: an integrative approach for identifying key molecular drivers from multi-omics assays;Singh;Bioinformatics,2019

5. Improved breast cancer prognosis through the combination of clinical and genetic markers;Sun;Bioinformatics,2007

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