Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
8051699 | Applied Mathematical Modelling | 2018 | 22 Pages |
Abstract
We first tested KPOCN using simulated datasets, and afterward, we applied this model to the real breast cancer datasets. KPOCN was shown to identify successfully key regulators with their corresponding response variables (targets) when using the simulated data, and identified well-known breast cancer oncogenes. These results demonstrated that our model can be used for an efficient identification of key genes that affect cancer development. Source codes are available at http://gcancer.org/KPOCN.
Keywords
Related Topics
Physical Sciences and Engineering
Engineering
Computational Mechanics
Authors
Bayarbaatar Amgalan, Ider Tseveendorj, Hyunju Lee,