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...
| Main Authors: | , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
American Scientific Publisher
2018
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| Subjects: | |
| Online Access: | http://umpir.ump.edu.my/id/eprint/19971/ http://umpir.ump.edu.my/id/eprint/19971/ http://umpir.ump.edu.my/id/eprint/19971/ 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/http://umpir.ump.edu.my/id/eprint/19971/
http://umpir.ump.edu.my/id/eprint/19971/
http://umpir.ump.edu.my/id/eprint/19971/1/43.%20An%20Improved%20Integrative%20Random%20Forest%20for%20Gene%20Regulatory%20Network%20Inference%20for%20Breast%20Cancer1.pdf