title: Visualization-aided classification ensembles discriminate lung adenocarcinoma and squamous cell carcinoma samples using their gene expression profiles.
abstract: BACKGROUND
  The widespread application of microarray experiments to cancer research is astounding including lung cancer, one of the most common fatal human tumors. Among non-small cell lung carcinoma (NSCLC), there are two major histological types of NSCLC, adenocarcinoma (AC) and squamous cell carcinoma (SCC).
  
  
  RESULTS
  In this paper, we proposed to integrate a visualization method called Radial Coordinate Visualization (Radviz) with a suitable classifier, aiming at discriminating two NSCLC subtypes using patients' gene expression profiles. Our analyses on simulated data and a real microarray dataset show that combining with a classification method, Radviz may play a role in selecting relevant features and ameliorating parsimony, while the final model suffers no or least loss of accuracy. Most importantly, a graphic representation is more easily understandable and implementable for a clinician than statistical methods and/or mathematic equations.
  
  
  CONCLUSIONS
  To conclude, using the NSCLC microarray data presented here as a benchmark, the comprehensive understanding of the underlying mechanism associated with NSCLC and of the mechanisms with its subtypes and respective stages will become reality in the near future.
authors.affiliation: Intensive Care Unit (ICU), First Hospital of Jilin University, Changchun, Jilin, China.
authors.forename: Ao
authors.initials: A
authors.lastname: Zhang
authors.affiliation: Department of Biostatistics and Markey Cancer Center, University of Kentucky, Lexington, Kentucky, United States of America.
authors.forename: Chi
authors.initials: C
authors.lastname: Wang
authors.affiliation: Intensive Care Unit (ICU), First Hospital of Jilin University, Changchun, Jilin, China.
authors.forename: Shiji
authors.initials: S
authors.lastname: Wang
authors.affiliation: LLX Solutions LLC., Waltham, Massachusetts, United States of America.
authors.forename: Liang
authors.initials: L
authors.lastname: Li
authors.affiliation: Intensive Care Unit (ICU), First Hospital of Jilin University, Changchun, Jilin, China.
authors.forename: Zhongmin
authors.initials: Z
authors.lastname: Liu
authors.affiliation: Division of Clinical Epidemiology, First Hospital of Jilin University, Changchun, Jilin, China.
authors.forename: Suyan
authors.initials: S
authors.lastname: Tian
mesh_terms: D000230:Adenocarcinoma / Q000175:diagnosis* / Q000235:genetics / Q000473:pathology; D014408:Biomarkers, Tumor / Q000235:genetics; D002294:Carcinoma, Squamous Cell / Q000175:diagnosis* / Q000235:genetics / Q000473:pathology; D003198:Computer Simulation; D003937:Diagnosis, Differential; D020869:Gene Expression Profiling; D015972:Gene Expression Regulation, Neoplastic; D006801:Humans; D008175:Lung Neoplasms / Q000175:diagnosis* / Q000235:genetics / Q000473:pathology
chemical_list: D014408:Biomarkers, Tumor