Topologically significant directed random walk with applied walker network in cancer environment.
Clicks: 181
ID: 55614
2019
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.
| Reference Key |
seah2019topologicallypakistan
Use this key to autocite in the manuscript while using
SciMatic Manuscript Manager or Thesis Manager
|
|---|---|
| Authors | Seah, Choon Sen;Kasim, Shahreen;Saedudin, Rd Rohmat;Md Fudzee, Mohd Farhan;Mohamad, Mohd Saberi;Hassan, Rohayanti;Ismail, Mohd Arfian; |
| Journal | pakistan journal of pharmaceutical sciences |
| Year | 2019 |
| DOI | DOI not found |
| URL | URL not found |
| Keywords |
Citations
No citations found. To add a citation, contact the admin at info@scimatic.org
Comments
No comments yet. Be the first to comment on this article.