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Identifying critical state of complex diseases by single-sample Kullback–Leibler divergence

BMC Genomics · 2020 · Vol. 21(1) · pp. 87–87
Jiayuan ZhongRui LiuPei Chen

Abstract

The proposed method effectively explores and quantifies the disturbance on the background caused by a case sample, and thus characterizes the criticality of a biological system. Our method not only identifies the critical state or tipping point at a single sample level, but also provides the sKLD-signaling markers for further practical application. It is therefore of great potential in personalized pre-disease diagnosis.

Ecosystem dynamics and resilienceMental Health Research TopicsGene Regulatory Network AnalysisDivergence (linguistics)Kullback–Leibler divergenceBiologyComputational biologySample (material)Evolutionary biologyDNA microarrayGeneticsStatisticsMathematics

MeSH terms

Disease SusceptibilityHumansSeverity of Illness IndexReproducibility of ResultsBiomarkersDisease ProgressionComputational BiologyGene Ontology

Funding

  • National Natural Science Foundation of China
  • China Postdoctoral Science Foundation
  • National Outstanding Youth Science Fund Project of National Natural Science Foundation of China
  • Fundamental Research Funds for the Central Universities
  • Basic and Applied Basic Research Foundation of Guangdong Province
Citations
473
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32.32
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100%
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