Topologically significant directed random walk with applied walker network in cancer environment

Choon Sen Seah, Shahreen Kasim, Rd Rohmat Saedudin, Mohd Farhan Md Fudzee, Mohd Saberi Mohamad, Rohayanti Hassan, Mohd Arfian Ismail

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)

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.

Original languageEnglish
Pages (from-to)1395-1408
Number of pages14
JournalPakistan Journal of Pharmaceutical Sciences
Volume32
Issue number3
Publication statusPublished - May 1 2019
Externally publishedYes

ASJC Scopus subject areas

  • Pharmaceutical Science

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