A Bayesian-based Approach for Identification of Potential Protein Biomarkers in Hepatocellular Carcinoma: 15th International Conference on Bioinformatics and Biomedical Technology, ICBBT 2023

Kangning Zhu; Jing Li; Boya Chen; Xin Liu

doi:10.1145/3608164.3608214

A Bayesian-based Approach for Identification of Potential Protein Biomarkers in Hepatocellular Carcinoma: 15th International Conference on Bioinformatics and Biomedical Technology, ICBBT 2023

Kangning Zhu, Jing Li, Boya Chen, Xin Liu^*

^*Corresponding author for this work

Xi'an Jiaotong-Liverpool University

Research output: Chapter in Book or Report/Conference proceeding › Conference Proceeding › peer-review

Original language	English
Title of host publication	2023 15th International Conference on Bioinformatics and Biomedical Technology, ICBBT 2023
Publisher	Association for Computing Machinery
Pages	110-119
Number of pages	10
ISBN (Electronic)	9798400700385
DOIs	https://doi.org/10.1145/3608164.3608214
Publication status	Published - 26 May 2023
Event	15th International Conference on Bioinformatics and Biomedical Technology, ICBBT 2023 - Xi'an, China Duration: 26 May 2023 → 28 May 2023

Publication series

Name	ACM International Conference Proceeding Series

Conference

Conference	15th International Conference on Bioinformatics and Biomedical Technology, ICBBT 2023
Country/Territory	China
City	Xi'an
Period	26/05/23 → 28/05/23

Keywords

Bayesian-based approach
Hepatocellular carcinoma
Machine learning
Potential biomarkers
Proteomic data

Access to Document

10.1145/3608164.3608214

http://www.scopus.com/inward/record.url?scp=85178263126&partnerID=8YFLogxK

Cite this

Zhu, K., Li, J., Chen, B., & Liu, X. (2023). A Bayesian-based Approach for Identification of Potential Protein Biomarkers in Hepatocellular Carcinoma: 15th International Conference on Bioinformatics and Biomedical Technology, ICBBT 2023. In 2023 15th International Conference on Bioinformatics and Biomedical Technology, ICBBT 2023 (pp. 110-119). (ACM International Conference Proceeding Series). Association for Computing Machinery. https://doi.org/10.1145/3608164.3608214

Zhu, Kangning ; Li, Jing ; Chen, Boya et al. / A Bayesian-based Approach for Identification of Potential Protein Biomarkers in Hepatocellular Carcinoma : 15th International Conference on Bioinformatics and Biomedical Technology, ICBBT 2023. 2023 15th International Conference on Bioinformatics and Biomedical Technology, ICBBT 2023. Association for Computing Machinery, 2023. pp. 110-119 (ACM International Conference Proceeding Series).

@inproceedings{d22e69431e514208a56aa2070cb8eabe,

title = "A Bayesian-based Approach for Identification of Potential Protein Biomarkers in Hepatocellular Carcinoma: 15th International Conference on Bioinformatics and Biomedical Technology, ICBBT 2023",

keywords = "Bayesian-based approach, Hepatocellular carcinoma, Machine learning, Potential biomarkers, Proteomic data",

author = "Kangning Zhu and Jing Li and Boya Chen and Xin Liu",

year = "2023",

month = may,

day = "26",

doi = "10.1145/3608164.3608214",

language = "English",

series = "ACM International Conference Proceeding Series",

publisher = "Association for Computing Machinery",

pages = "110--119",

booktitle = "2023 15th International Conference on Bioinformatics and Biomedical Technology, ICBBT 2023",

note = "15th International Conference on Bioinformatics and Biomedical Technology, ICBBT 2023 ; Conference date: 26-05-2023 Through 28-05-2023",

}

Zhu, K, Li, J, Chen, B & Liu, X 2023, A Bayesian-based Approach for Identification of Potential Protein Biomarkers in Hepatocellular Carcinoma: 15th International Conference on Bioinformatics and Biomedical Technology, ICBBT 2023. in 2023 15th International Conference on Bioinformatics and Biomedical Technology, ICBBT 2023. ACM International Conference Proceeding Series, Association for Computing Machinery, pp. 110-119, 15th International Conference on Bioinformatics and Biomedical Technology, ICBBT 2023, Xi'an, China, 26/05/23. https://doi.org/10.1145/3608164.3608214

A Bayesian-based Approach for Identification of Potential Protein Biomarkers in Hepatocellular Carcinoma: 15th International Conference on Bioinformatics and Biomedical Technology, ICBBT 2023. / Zhu, Kangning; Li, Jing; Chen, Boya et al.
2023 15th International Conference on Bioinformatics and Biomedical Technology, ICBBT 2023. Association for Computing Machinery, 2023. p. 110-119 (ACM International Conference Proceeding Series).

Research output: Chapter in Book or Report/Conference proceeding › Conference Proceeding › peer-review

TY - GEN

T1 - A Bayesian-based Approach for Identification of Potential Protein Biomarkers in Hepatocellular Carcinoma

T2 - 15th International Conference on Bioinformatics and Biomedical Technology, ICBBT 2023

AU - Zhu, Kangning

AU - Li, Jing

AU - Chen, Boya

AU - Liu, Xin

PY - 2023/5/26

Y1 - 2023/5/26

KW - Bayesian-based approach

KW - Hepatocellular carcinoma

KW - Machine learning

KW - Potential biomarkers

KW - Proteomic data

UR - http://www.scopus.com/inward/record.url?scp=85178263126&partnerID=8YFLogxK

U2 - 10.1145/3608164.3608214

DO - 10.1145/3608164.3608214

M3 - Conference Proceeding

AN - SCOPUS:85178263126

T3 - ACM International Conference Proceeding Series

SP - 110

EP - 119

BT - 2023 15th International Conference on Bioinformatics and Biomedical Technology, ICBBT 2023

PB - Association for Computing Machinery

Y2 - 26 May 2023 through 28 May 2023

ER -

Zhu K, Li J, Chen B, Liu X. A Bayesian-based Approach for Identification of Potential Protein Biomarkers in Hepatocellular Carcinoma: 15th International Conference on Bioinformatics and Biomedical Technology, ICBBT 2023. In 2023 15th International Conference on Bioinformatics and Biomedical Technology, ICBBT 2023. Association for Computing Machinery. 2023. p. 110-119. (ACM International Conference Proceeding Series). doi: 10.1145/3608164.3608214

A Bayesian-based Approach for Identification of Potential Protein Biomarkers in Hepatocellular Carcinoma: 15th International Conference on Bioinformatics and Biomedical Technology, ICBBT 2023

Publication series

Conference

Keywords

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