Learning Association Characteristics by Dynamic Hypergraph and Gated Convolution Enhanced Pairwise Attributes for Prediction of Disease-Related lncRNAs-Reference-Cited by-同舟云学术

Learning Association Characteristics by Dynamic Hypergraph and Gated Convolution Enhanced Pairwise Attributes for Prediction of Disease-Related lncRNAs

Published:2024-03-25 Issue:8 Volume:64 Page:3569-3578
ISSN:1549-9596
Container-title:Journal of Chemical Information and Modeling
language:en
Short-container-title:J. Chem. Inf. Model.

Author:

Xuan Ping¹²^ORCID,Lu Siyuan¹,Cui Hui³,Wang Shuai⁴^ORCID,Nakaguchi Toshiya⁵,Zhang Tiangang¹⁶

Affiliation:

1. School of Computer Science and Technology, Heilongjiang University, Harbin 150080, China

2. Department of Computer Science, Shantou University, Shantou 515063, China

3. Department of Computer Science and Information Technology, La Trobe University, Melbourne 3083, Australia

4. School of Information Science and Engineering, Yanshan University, Qinhuangdao 066004, China

5. Center for Frontier Medical Engineering, Chiba University, Chiba 2638522, Japan

6. School of Mathematical Science, Heilongjiang University, Harbin 150080, China

Funder

Natural Science Foundation of Heilongjiang Province

Shantou University

National Natural Science Foundation of China

Publisher

American Chemical Society (ACS)

Link

https://pubs.acs.org/doi/pdf/10.1021/acs.jcim.4c00245

Reference44 articles.

1. LNCcation: lncRNA localization and function

2. Role of lncRNA LUCAT1 in cancer

3. The how and why of lncRNA function: An innate immune perspective

4. Comprehensive analysis of cuproptosis-related lncRNAs in immune infiltration and prognosis in hepatocellular carcinoma

5. Computational Approaches for Functional Prediction and Characterisation of Long Noncoding RNAs

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