Driver Attribute Filling for Genes in Interaction Network via Modularity Subspace-Based Concept Learning from Small Samples
The aberrations of a gene can influence it and the functions of its neighbour genes in gene interaction network, leading to the development of carcinogenesis of normal cells. In consideration of gene interaction network as a complex network, previous studies have made efforts on the driver attribute...
Main Authors: | Fei Xie, Jianing Xi, Qun Duan |
---|---|
Format: | Article |
Language: | English |
Published: |
Hindawi-Wiley
2020-01-01
|
Series: | Complexity |
Online Access: | http://dx.doi.org/10.1155/2020/6643551 |
Similar Items
-
Attribute based Subspace Learning
by: Hung-Kai Wang, et al.
Published: (2016) -
Providing an optimized model to detect driver genes from heterogeneous cancer samples using restriction in subspace learning
by: Ali Reza Ebadi, et al.
Published: (2021-04-01) -
An experimental study of the fluid mechanics of filling a small part of modular mold
by: Miller, Mark Wade, 1967-
Published: (2013) -
Regular and Irregular Sampling Theorem for Multiwavelet Subspaces
by: Liu Zhanwei, et al.
Published: (2010-01-01) -
A Study on the Subspace LDA Methods for Solving the Small Sample Size Problem in Face Recognition
by: Huang, Ching-Ting, et al.
Published: (2014)