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Izvorni znanstveni članak
https://doi.org/10.20532/cit.2019.1004856

Identification of Novel Cancer-Related Genes with a Prognostic Role Using Gene Expression and Protein-Protein Interaction Network Data

Peng Li ; Beijing Normal University, China
Bo Sun ; Beijing Normal University, China
Maozu Guo ; Beijing University of Civil Engineering and Architecture, China

Puni tekst: engleski, pdf (1 MB) str. 57-71 preuzimanja: 17* citiraj
APA 6th Edition
Li, P., Sun, B. i Guo, M. (2019). Identification of Novel Cancer-Related Genes with a Prognostic Role Using Gene Expression and Protein-Protein Interaction Network Data. Journal of computing and information technology, 27 (3), 57-71. https://doi.org/10.20532/cit.2019.1004856
MLA 8th Edition
Li, Peng, et al. "Identification of Novel Cancer-Related Genes with a Prognostic Role Using Gene Expression and Protein-Protein Interaction Network Data." Journal of computing and information technology, vol. 27, br. 3, 2019, str. 57-71. https://doi.org/10.20532/cit.2019.1004856. Citirano 08.07.2020.
Chicago 17th Edition
Li, Peng, Bo Sun i Maozu Guo. "Identification of Novel Cancer-Related Genes with a Prognostic Role Using Gene Expression and Protein-Protein Interaction Network Data." Journal of computing and information technology 27, br. 3 (2019): 57-71. https://doi.org/10.20532/cit.2019.1004856
Harvard
Li, P., Sun, B., i Guo, M. (2019). 'Identification of Novel Cancer-Related Genes with a Prognostic Role Using Gene Expression and Protein-Protein Interaction Network Data', Journal of computing and information technology, 27(3), str. 57-71. https://doi.org/10.20532/cit.2019.1004856
Vancouver
Li P, Sun B, Guo M. Identification of Novel Cancer-Related Genes with a Prognostic Role Using Gene Expression and Protein-Protein Interaction Network Data. Journal of computing and information technology [Internet]. 2019 [pristupljeno 08.07.2020.];27(3):57-71. https://doi.org/10.20532/cit.2019.1004856
IEEE
P. Li, B. Sun i M. Guo, "Identification of Novel Cancer-Related Genes with a Prognostic Role Using Gene Expression and Protein-Protein Interaction Network Data", Journal of computing and information technology, vol.27, br. 3, str. 57-71, 2019. [Online]. https://doi.org/10.20532/cit.2019.1004856

Sažetak
Early cancer diagnosis and prognosis prediction are necessary for cancer patients. Effective identification of cancer-related genes and biomarkers and survival prediction for cancer patients would facilitate personalized treatment of cancer patients. This study aimed to investigate a method for integrating data regarding gene expression and protein-protein interaction networks to identify cancer-related prognostic genes via random walk with restart algorithm and survival analysis. Known cancer-related genes in protein-protein interaction networks were considered seed genes, and the random walk algorithm was used to identify candidate cancer-related genes. Thereafter, using the univariant Cox regression model, gene expression data were screened to identify survival-related genes. Furthermore, candidate genes and survival-related genes were screened to identify cancer-related prognostic genes. Finally, the effectiveness of the method was verified through gene function analysis and survival prediction. The results indicate that the cancer-related genes can be considered prognostic cancer biomarkers and provide a basis for cancer diagnosis.

Ključne riječi
cancer genes, random walk algorithm, PPIN, survival analysis, biomarkers

Hrčak ID: 237993

URI
https://hrcak.srce.hr/237993

Posjeta: 29 *