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  • 标题:Classification of Schizophrenia Patients by Using Genomic Data: A Data Mining Approach
  • 本地全文:下载
  • 作者:Kaan Yilancioglu ; Muhsin Konuk
  • 期刊名称:The Journal of Neurobehavioral Sciences
  • 电子版ISSN:2148-4325
  • 出版年度:2015
  • 卷号:2
  • 期号:3
  • 页码:102-104
  • DOI:10.5455/JNBS.1446109872
  • 出版社:International Medical Journal Management and Indexing System
  • 摘要:Genomic information obtained from robust analysis methods such as microarray and next generation sequencing reveals underlying disease mediating factors and potential diagnostic biomarkers. Data mining methods have been widely chosen for classification and regression studies on the health investigations as well as other disciplines since it’s born. In the present study, public Gene Expression Omnibus (GEO) genome wide expression dataset (ID: GSE12679) consisting of mRNA transcripts of post-mortem brain tissues in schizophrenic and normal patients were analyzed by using Multilayer Perceptron Neural Network (MLP NN) algorithm. A set of most differentially expressed genetic features (p
  • 关键词:Data Mining; Schizophrenia; Neural Network
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