array(2) { ["lab"]=> string(4) "1409" ["publication"]=> string(5) "12656" } Cancer classification and biomarker selection via a penalized logsum network-based logistic regression model - Liang Yong | LabXing

Cancer classification and biomarker selection via a penalized logsum network-based logistic regression model

2021
期刊 Technology and Health Care
BACKGROUND: In genome research, it is particularly important to identify molecular biomarkers or signaling pathways related to phenotypes. Logistic regression model is a powerful discrimination method that can offer a clear statistical explanation and obtain the classification probability of classification label information. However, it is unable to fulfill biomarker selection. OBJECTIVE: The aim of this paper is to give the model efficient gene selection capability. METHODS: In this paper, we propose a new penalized logsum network-based regularization logistic regression model for gene selection and cancer classification. RESULTS: Experimental results on simulated data sets show that our method is effective in the analysis of high-dimensional data. For a large data set, the proposed method has achieved 89.66%(training) and 90.02%(testing) AUC performances, which are, on average, 5.17%(training) and 4.49 …

  • 期 Preprint
  • 页码 1-9
  • IOS Press