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Article: A Pseudotemporal Causality-based Bayesian Approach to Identify EMT-associated Regulatory Relationships of AS events and RBPs During Breast Cancer Progression

TitleA Pseudotemporal Causality-based Bayesian Approach to Identify EMT-associated Regulatory Relationships of AS events and RBPs During Breast Cancer Progression
Authors
Issue Date31-Jul-2023
PublisherPublic Library of Science
Citation
PLoS Computational Biology, 2023, v. 19, n. 3 How to Cite?
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.


Persistent Identifierhttp://hdl.handle.net/10722/330937
ISSN
2023 Impact Factor: 3.8
2023 SCImago Journal Rankings: 1.652
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorSun, LJ-
dc.contributor.authorQiu, YS-
dc.contributor.authorChing, WK-
dc.contributor.authorZhao, P-
dc.contributor.authorZou, Q-
dc.date.accessioned2023-09-21T06:51:17Z-
dc.date.available2023-09-21T06:51:17Z-
dc.date.issued2023-07-31-
dc.identifier.citationPLoS Computational Biology, 2023, v. 19, n. 3-
dc.identifier.issn1553-734X-
dc.identifier.urihttp://hdl.handle.net/10722/330937-
dc.description.abstract<p>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: <a href="http://hkumath.hku.hk/~wkc/PCB(data+code).zip">http://hkumath.hku.hk/~wkc/PCB(data+code).zip</a>.<br></p>-
dc.languageeng-
dc.publisherPublic Library of Science-
dc.relation.ispartofPLoS Computational Biology-
dc.titleA Pseudotemporal Causality-based Bayesian Approach to Identify EMT-associated Regulatory Relationships of AS events and RBPs During Breast Cancer Progression-
dc.typeArticle-
dc.identifier.doi10.1371/journal.pcbi.1010939-
dc.identifier.scopuseid_2-s2.0-85151312893-
dc.identifier.volume19-
dc.identifier.issue3-
dc.identifier.eissn1553-7358-
dc.identifier.isiWOS:000956087800002-
dc.identifier.issnl1553-734X-

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