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...

وصف كامل

التفاصيل البيبلوغرافية
المؤلفون الرئيسيون: Chandran, Suntharaamurthi, Kohbalan, Moorthy, Mohd Arfian, Ismail, Mohd Zamri, Osman, Mohd Azwan Mohamad, Hamza, Ernawan, Ferda
التنسيق: مقال
اللغة:English
منشور في: American Scientific Publisher 2018
الموضوعات:
QA76 Computer software
الوصول للمادة أونلاين:http://umpir.ump.edu.my/id/eprint/19971/1/43.%20An%20Improved%20Integrative%20Random%20Forest%20for%20Gene%20Regulatory%20Network%20Inference%20for%20Breast%20Cancer1.pdf

الانترنت

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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