PCB: A pseudotemporal causality-based Bayesian approach to identify EMT-associated regulatory relationships of AS events and RBPs during breast cancer progression
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Published:2023-03-17
Issue:3
Volume:19
Page:e1010939
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ISSN:1553-7358
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Container-title:PLOS Computational Biology
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language:en
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Short-container-title:PLoS Comput Biol
Author:
Sun Liangjie,
Qiu YushanORCID,
Ching Wai-Ki,
Zhao Pu,
Zou QuanORCID
Abstract
During breast cancer metastasis, the developmental process epithelial-mesenchymal (EM) transition is abnormally activated. Transcriptional regulatory networks controlling EM transition are well-studied; however, alternative RNA splicing also plays a critical regulatory role during this process. Alternative splicing was proved to control the EM transition process, and RNA-binding proteins were determined to regulate alternative splicing. A comprehensive understanding of alternative splicing and the RNA-binding proteins that regulate it during EM transition and their dynamic impact on breast cancer remains largely unknown. To accurately study the dynamic regulatory relationships, time-series data of the EM transition process are essential. However, only cross-sectional data of epithelial and mesenchymal specimens are available. Therefore, we developed a pseudotemporal causality-based Bayesian (PCB) approach to infer the dynamic regulatory relationships between alternative splicing events and RNA-binding proteins. Our study sheds light on facilitating the regulatory network-based approach to identify key RNA-binding proteins or target alternative splicing events for the diagnosis or treatment of cancers. The data and code for PCB are available at: http://hkumath.hku.hk/~wkc/PCB(data+code).zip.
Funder
National Natural Science Foundation of China
Basic and Applied Basic Research Foundation of Guangdong Province
Hong Kong RGC GRF Grant
Special Funds for the Basic Research and Development Program in the Central Non-profit Research Institutesof China
Special Projects of the Central Government in Guidance of Local Science and Technology Development
Publisher
Public Library of Science (PLoS)
Subject
Computational Theory and Mathematics,Cellular and Molecular Neuroscience,Genetics,Molecular Biology,Ecology,Modeling and Simulation,Ecology, Evolution, Behavior and Systematics
Cited by
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