Using Multi-objective Optimization to Identify Dynamical Network Biomarkers as Early-warning Signals of Complex Diseases

Scientific Reports
Fatemeh Vafaee

Abstract

Biomarkers have gained immense scientific interest and clinical value in the practice of medicine. With unprecedented advances in high-throughput technologies, research interest in identifying novel and customized disease biomarkers for early detection, diagnosis, or drug responses is rapidly growing. Biomarkers can be identified in different levels of molecular biomarkers, networks biomarkers and dynamical network biomarkers (DNBs). The latter is a recently developed concept which relies on the idea that a cell is a complex system whose behavior is emerged from interplay of various molecules, and this network of molecules dynamically changes over time. A DNB can serve as an early-warning signal of disease progression, or as a leading network that drives the system into the disease state, and thus unravels mechanisms of disease initiation and progression. It is therefore of great importance to identify DNBs efficiently and reliably. In this work, the problem of DNB identification is defined as a multi-objective optimization problem, and a framework to identify DNBs out of time-course high-throughput data is proposed. Temporal gene expression data of a lung injury with carbonyl chloride inhalation exposure has been used as a cas...Continue Reading

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Citations

Aug 25, 2017·Computational and Mathematical Methods in Medicine·Gang WangXiufen Zou
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Datasets Mentioned

BETA
GSE2565

Software Mentioned

ClusterONE
Cytoscape
NSGA
FpClass
BiNGO
ORTI
II

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