Name
Abstract | ||
|---|---|---|
In this paper, based on robust PCA, a novel method of characteristic genes identification is proposed. In our method, the differentially expressed genes and non-differentially expressed genes are treated as perturbation signals S0 and low-rank matrix A0, respectively, which can be recovered from the gene expression data using robust PCA. The scheme to identify the characteristic genes is as following. Firstly, the matrix S0 of perturbation signals is discovered from gene expression data matrix D by using robust PCA. Secondly, the characteristic genes are selected according to matrix S0. Finally, the characteristic genes are checked by the tool of Gene Ontology. The experimental results show that our method is efficient and effective. © 2012 Springer-Verlag. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1007/978-3-642-31837-5_25 | Communications in Computer and Information Science |
Keywords | Field | DocType |
robust PCA,gene identification,gene expression data | Gene,Pattern recognition,Computer science,Gene ontology,Matrix (mathematics),Gene expression,Robust principal component analysis,Artificial intelligence | Conference |
Volume | ISSN | Citations |
304 CCIS | 1865-0929 | 0 |
PageRank | References | Authors |
0.34 | 6 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Chun-hou Zheng | 1 | 732 | 71.79 |
| Liu Jin-Xing | 2 | 40 | 16.11 |
| Jian-Xun Mi | 3 | 162 | 9.79 |
| Xu Yong | 4 | 2119 | 73.51 |