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  • 标题:A Constrained NMF Approach to Analyze Quantitative Metagenomic Data * * Sebastien Raguideau is funded by a phD grant of the Meta-omics and Microbial Ecosystems (MME) program of INRA.
  • 本地全文:下载
  • 作者:Sébastien Raguideau ; Béatrice Laroche ; Marion Leclerc
  • 期刊名称:IFAC PapersOnLine
  • 印刷版ISSN:2405-8963
  • 出版年度:2016
  • 卷号:49
  • 期号:26
  • 页码:71-76
  • DOI:10.1016/j.ifacol.2016.12.105
  • 语种:English
  • 出版社:Elsevier
  • 摘要:In this paper, we propose a new method for inferring the metabolic potential of microbial ecosystems based on gene frequencies generated from shotgun metagenomic data. Our approach is based on Non-Negative Matrix Factorization with constraints accounting for prior biological knowledge of bacterial metabolism. The problem is solved using efficient accelerated projected gradient methods. The approach is illustrated on a toy model and on real data on fiber metabolism by the gut microbiota in humans. We show how this approach leads to the inference of biologically relevant gene clusters.
  • 关键词:Data reductionNon-Negative Matrix FactorizationMetagenomicsMicrobial ecosystemsGutSupervised Machine Learning
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