Name
Abstract | ||
|---|---|---|
The proposed AUCTSP is a simple yet reliable and robust rank-based classifier for gene expression classification. While the AUCTSP works by the same principle as TSP, its ability to determine the top scoring gene pair based on the relative rankings of two marker genes across all subjects as opposed to each individual subject results in significant performance gains in classification accuracy. In addition, the proposed method tends to avoid selection of non-informative (pivot) genes as members of the top-scoring pair. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1186/s12859-018-2231-1 | BMC Bioinformatics |
Keywords | Field | DocType |
AUC,Breast cancer,Colon cancer,Diffuse large B-Cell lymphoma,Gene expression,Gene selection,Leukemia,Microarray data analysis,Ovarian cancer,Prostate cancer,Receiver operating characteristic (ROC) curve | Decision rule,Biological plausibility,Receiver operating characteristic,Ranking,Expression (mathematics),Pattern recognition,Biology,Artificial intelligence,Overfitting,Classifier (linguistics),Genetics,Estimator | Journal |
Volume | Issue | ISSN |
19 | 1 | 1471-2105 |
Citations | PageRank | References |
1 | 0.39 | 7 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| D. Nikolos | 1 | 291 | 31.38 |
| Alireza Khamesipour | 2 | 1 | 0.72 |
| Constantin T. Yiannoutsos | 3 | 34 | 5.95 |