Detecting Early Warning Signal of Influenza A Disease Using Sample-Specific Dynamical Network Biomarkers.

<italic>Aims/Introduction</italic>. Evidences have shown that the deteriorated procession of disease is not a smooth change with time and conditions, in which a critical transition point denoted as predisease state drives the state from normal to disease. Considering individual differences, this pap...

Descripción completa

Detalles Bibliográficos
Publicado en:BioMed Research International Vol. 2018; pp. 1 - 8
Autores principales: Zhu, Shanshan, Gao, Jie, Ding, Tao, Xu, Junhua, Wu, Min
Formato: equations & formulas research tables/charts Journal Article
Publicado: Wiley-Blackwell 1/31/2018
Acceso en línea:Ver este registro en EBSCOhost
fields @attributes:
  recordID: 1
pdfLink:
plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=127695521&site=ehost-live
header:
  @attributes:
    shortDbName: ccm
    uiTerm: 127695521
    longDbName: CINAHL Complete
    uiTag: AN
  controlInfo:
    bkinfo:
    dissinfo:
    jinfo:
      jid:
        23146133
        FT2T
      jtl: BioMed Research International
      issn: 23146133
      maglogo: N
    pubinfo:
      dt: 1/31/2018
      vid: 2018
      pid: 480
      pub: Wiley-Blackwell
      place: Malden, Massachusetts
    artinfo:
      ui:
        127695521
        127695521
        127695521
        10.1155/2018/6807059
        127695521
      ppf: 1
      ppct: 7
      formats:
        fmt:
          – @attributes:
              type: T
          – @attributes:
              type: P
      tig:
        atl: Detecting Early Warning Signal of Influenza A Disease Using Sample-Specific Dynamical Network Biomarkers.
      aug:
        au:
          Zhu, Shanshan
          Gao, Jie
          Ding, Tao
          Xu, Junhua
          Wu, Min
        affil: School of Science, Jiangnan University, Wuxi 214122, China
      sug:
        subj:
          Influenza Symptoms
          Biological Markers
          Human
          Influenza Physiopathology
          Influenza Risk Factors
          Genes
          Data Analysis Software
          Gene Expression
          T-Tests
      ab: <italic>Aims/Introduction</italic>. Evidences have shown that the deteriorated procession of disease is not a smooth change with time and conditions, in which a critical transition point denoted as predisease state drives the state from normal to disease. Considering individual differences, this paper provides a sample-specific method that constructs an index with individual-specific dynamical network biomarkers (DNB) which are defined as early warning index (EWI) for detecting predisease state of individual sample. Based on microarray data of influenza A disease, 144 genes are selected as DNB and the 7th time period is defined as predisease state. In addition, according to functional analysis of the discovered DNB, it is relevant with experience data, which can illustrate the effectiveness of our sample-specific method.
      pubtype: Academic Journal
      doctype:
        equations & formulas
        research
        tables/charts
        Journal Article
      ougenre: Article
    language: English
    refInfo:
    holdings:
      @attributes:
        islocal: N