Please use this identifier to cite or link to this item: http://localhost:80/xmlui/handle/123456789/14691
Title: Topologically significant directed random walk with applied walker network in cancer environment
Authors: Seah, Choon Sen
Kasim, Shahreen
Saedudin, Rd Rohmat
Md Fudzee, Mohd Farhan
Mohamad, Mohd Saberi
Hassan, Rohayanti
Ismail, Mohd Arfian
Keywords: Significant directed random walk
cancer classification
gene expression dataset
walker network.
Issue Date: 18-May-2019
Publisher: Karachi: Faculty of Pharmacy & Pharmaceutical Sciences, Karachi
Citation: Seah, C. S., Kasim, S., Saedudin, R. R., Fudzee, M., Farhan, M., Mohamad, M. S., ... & Ismail, M. A. (2019). Topologically significant directed random walk with applied walker network in cancer environment. Pakistan journal of pharmaceutical sciences, 32.
Abstract: Numerous cancer studies have combined different datasets for the prognosis of patients. This study incorporated four networks for significant directed random walk (sDRW) to predict cancerous genes and risk pathways. The study investigated the feasibility of cancer prediction via different networks. In this study, multiple micro array data were analysed and used in the experiment. Six gene expression datasets were applied in four networks to study the effectiveness of the networks in sDRW in terms of cancer prediction. The experimental results showed that one of the proposed networks is outstanding compared to other networks. The network is then proposed to be implemented in sDRW as a walker network. This study provides a foundation for further studies and research on other networks. We hope these finding will improve the prognostic methods of cancer patients.
URI: http://142.54.178.187:9060/xmlui/handle/123456789/14691
ISSN: 1011-601X
Appears in Collections:Issue 3 (Special)

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