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...

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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
Descripción
Sumario:<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.