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BioMed Research International
Volume 2018, Article ID 6807059, 7 pages
https://doi.org/10.1155/2018/6807059
Research Article

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

School of Science, Jiangnan University, Wuxi 214122, China

Correspondence should be addressed to Jie Gao; nc.ude.nangnaij@eijoag

Received 5 September 2017; Revised 30 November 2017; Accepted 25 December 2017; Published 31 January 2018

Academic Editor: Yudong Cai

Copyright © 2018 Shanshan Zhu et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Aims/Introduction. 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.