An Improved Integrative Random Forest for Gene Regulatory Network Inference of Breast Cancer

An Improved Integrative Random Forest for Gene Regulatory Network Inference of Breast Cancer

Gene Regulatory Network (GRN) inference aims to capture the regulatory influences between the genes and regulatory events in the GRN. Integrative Random Forest for Gene Regulatory Network Inference (iRafNet) is a RF based algorithm which provides a great result in constructing GRN inference by integ...

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Bibliographic Details
Main Authors: Chandran, Suntharaamurthi, Kohbalan, Moorthy, Mohd Arfian, Ismail, Mohd Zamri, Osman, Mohd Azwan Mohamad, Hamza, Ernawan, Ferda
Format: Article
Language:English
Published: American Scientific Publisher 2018
Subjects:
QA76 Computer software
Online Access:http://umpir.ump.edu.my/id/eprint/19971/1/43.%20An%20Improved%20Integrative%20Random%20Forest%20for%20Gene%20Regulatory%20Network%20Inference%20for%20Breast%20Cancer1.pdf

Internet

http://umpir.ump.edu.my/id/eprint/19971/1/43.%20An%20Improved%20Integrative%20Random%20Forest%20for%20Gene%20Regulatory%20Network%20Inference%20for%20Breast%20Cancer1.pdf

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