Art
J-GLOBAL ID:202102283004597921   Reference number:21A0084022

Inference of Genetic Networks From Time-Series and Static Gene Expression Data: Combining a Random-Forest-Based Inference Method With Feature Selection Methods

時系列および静的遺伝子発現データからの遺伝的ネットワークの推論:ランダムフォレストベース推論法と特徴選択法の結合【JST・京大機械翻訳】
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Material:
Volume: 11  Page: 595912  Publication year: 2020 
JST Material Number: U7071A  ISSN: 1664-8021  Document type: Article
Article type: 原著論文  Country of issue: Switzerland (CHE)  Language: ENGLISH (EN)
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Molecular and genetic information processing  ,  Gene expression  ,  Research methods in genetics  ,  Artificial intelligence 
Reference (28):
  • BreimanL. (2001). Random forests. Mach. Learn. 45, 5-32. doi: 10.1023/A:1010933404324
  • CaiJ.KuoJ.WangS.YangS. (2018). Feature selection in machine learning: a new perspective. Neurocomputing 300, 70-79. doi: 10.1016/j.neucom.2017.11.077
  • ChouI. C.VoitE. O. (2009). Recent developments in parameter estimation and structure identification of biochemical and genomic systems. Math. Biosci. 219, 57-83. doi: 10.1016/j.mbs.2009.03.00219327372
  • ClevelandW. S. (1979). Robust locally weight regression and smoothing scatterplots. J. Am. Stat. Assoc. 79, 829-836. doi: 10.1080/01621459.1979.10481038
  • de Matos SimoesR.Emmert-StreibF. (2012). Bagging statistical network inference from large-scale gene expression data. PLoS ONE 7:e33624. doi: 10.1371/journal.pone.003362422479422
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