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Identification of the gene signature reflecting schizophrenia's etiology by constructing artificial intelligence-based method of enhanced reproducibility.

Qing-Xia YangYun-Xia WangFeng-Cheng LiSong ZhangYong-Chao LuoYi LiJing TangBo LiYu-Zong ChenWei-Wei XueJian Zhang
Published in: CNS neuroscience & therapeutics (2019)
A new strategy capable of enhancing the reproducibility of feature selection in current SZ research was successfully constructed and validated. A group of candidate genes identified in this study should be considered as great potential for revealing the etiology of SZ.
Keyphrases
  • artificial intelligence
  • machine learning
  • deep learning
  • big data
  • wastewater treatment
  • genome wide
  • copy number
  • gene expression
  • climate change