Biotechnology Letters

, Volume 39, Issue 12, pp 1835–1842 | Cite as

Characterization of biomarkers in stroke based on ego-networks and pathways

Original Research Paper

Abstract

Objective

To explore potential biomarkers in stroke based on ego-networks and pathways.

Results

EgoNet method was applied to search for the underlying biomarkers in stroke using transcription profiling of E-GEOD-58294 and protein–protein interaction (PPI) data. Eight ego-genes were identified from PPI network according to the degree characteristics at the criteria of top 5% ranked z-sore and degree >1. Eight candidate ego-networks with classification accuracy ≥0.9 were selected. After performed randomization test, seven significant ego-networks with adjusted p value < 0.05 were identified. Pathway enrichment analysis was then conducted with these ego-networks to search for the significant pathways. Finally, two significant pathways were identified, and six of seven ego-networks were enriched to “3′-UTR-mediated translational regulation” pathway, indicating that this pathway performs an important role in the development of stroke.

Conclusions

Seven ego-networks were constructed using EgoNet and two significant enriched by pathways were identified. These may provide new insights into the potential biomarkers for the development of stroke.

Keywords

Ego-gene Ego-network Pathway Stroke 

Notes

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

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Copyright information

© Springer Science+Business Media B.V. 2017

Authors and Affiliations

  1. 1.Department of NeurologyThe 2nd People’s Hospital of LiaochengLiaochengPeople’s Republic of China

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