Specific tuning parameter for directed random walk algorithm cancer classification

Seah, Choon Sen and Kasim, Shahreen and Mohamad, Mohd Saberi (2017) Specific tuning parameter for directed random walk algorithm cancer classification. International Journal on Advanced Science, Engineering and Information Technology, 7 (1). pp. 176-182. ISSN 20885334

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Official URL: http://dx.doi.org/10.18517/ijaseit.7.1.1588

Abstract

Accuracy of cancerous gene classification is a central challenge in clinical cancer research. Microarray-based gene biomarkers have proved the performance and its ability over traditional clinical parameters. However, gene biomarkers of an individual are less robustness due to litter reproducibility between different cohorts of patients. Several methods incorporating pathway information such as directed random walk have been proposed to infer the pathway activity. This paper discusses the implementation of group specific tuning parameter in directed random walk algorithm. In this experiment, gene expression data and pathway data are used as input data. Throughout this experiment, more significant pathway activities can be identified which increases the accuracy of cancer classification. The lung cancer gene is used as the experimental dataset, with which, the sDRW is used in determining significant pathways. More risk-active pathways are identified throughout this experiment.

Item Type:Article
Uncontrolled Keywords:Directed random walk algorithm; group specific tuning parameter; cancer classification
Subjects:R Medicine > RC Internal medicine > RC0254 Neoplasms. Tumors. Oncology (including Cancer)
Divisions:Faculty of Computer Science and Information Technology > Department of Web Technology
ID Code:10360
Deposited By:Mr. Mohammad Shaifulrip Ithnin
Deposited On:06 Sep 2018 09:58
Last Modified:06 Sep 2018 09:58

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