title: Minimal gene selection for classification and diagnosis prediction based on gene expression profile.
abstract: BACKGROUND
  Up to date different methods have been used in order to dimensions reduction, classification, clustering and prediction of cancers based on gene expression profiling. The aim of this study is extracting most significant genes and classifying of Diffuse Large B-cell Lymphoma (DLBCL) patients on the basis of their gene expression profiles.
  
  
  METHODS
  We studied 40 DLBCL patients and 4026 genes. We utilized Artificial Neural Network (ANN) for classification of patients in two groups: Germinal center and Activated like. As we were faced with low number of patients (40) and numerous genes (4026), we tried to deploy one optimum network and achieve to minimum error. Moreover we used signal to noise (S/N) ratio as a main tool for dimension reduction. We tried to select suitable training data and so to train just one network instead of 26 networks. Finally, we extracted two most significant genes.
  
  
  RESULTS
  In this study two most significant genes based on their S/N ratios were selected. After selection of suitable training samples, the training and testing error were 0 and 7% respectively.
  
  
  CONCLUSIONS
  We have shown that the use of two most significant genes based on their S/N ratios and selection of suitable training samples can lead to classify DLBCL patients with a rather good result. Actually with the aid of mentioned methods we could compensate lack of enough number of patients, improve accuracy of classifying and reduce complication of computations and so running time.
authors: Medical School, Medical Physics and Engineering, Medical Image and Signal Processing Research Center, Isfahan, Iran ; Medical School, Medical Physics and Engineering, Isfahan University of Medical Sciences, Isfahan, Iran.
authors: Alireza
authors: A
authors: Mehridehnavi
authors: Lia
authors: L
authors: Ziaei
keywords: Artificial neural network; classification; diffuse large B-cell lymphoma; dimension reduction; significant genes
references: Biometrics. 2002 Dec;58(4):701-17
references: 12495124
references: Nature. 2000 Feb 3;403(6769):503-11
references: 10676951
references: BMC Bioinformatics. 2003 Apr 10;4:13
references: 12697066
references: Nat Med. 2001 Jun;7(6):673-9
references: 11385503
references: Clin Lymphoma. 2004 Sep;5(2):128-9
references: 15453930
references: Science. 1999 Oct 15;286(5439):531-7
references: 10521349
references: N Engl J Med. 2004 Apr 29;350(18):1828-37
references: 15115829
references: Genome Inform. 2001;12:14-23
references: 11791220