Systematic Characterization and Prediction of Human Hypertension Genes

  • Yan Hui Li*
  • , Gai Gai Zhang
  • , Nanping Wang
  • *Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

13 Scopus citations

Abstract

Hypertension is a major cardiovascular risk factor and accounts for a large part of cardiovascular mortality. In this work, we analyzed the properties of hypertension genes and found that when compared with genes not yet known to be involved in hypertension regulation, known hypertension genes display distinguishing features: (1) hypertension genes tend to be located at network center; (2) hypertension genes tend to interact with each other; and (3) hypertension genes tend to enrich in certain biological processes and show certain phenotypes. Based on these features, we developed a machine-learning algorithm to predict new hypertension genes. One hundred and seventy-seven candidates were predicted with a posterior probability >0.9. Evidence supporting 17 of the predictions has been found.

Original languageEnglish
Pages (from-to)349-355
Number of pages7
JournalHypertension
Volume69
Issue number2
DOIs
StatePublished - 1 Feb 2017
Externally publishedYes

Keywords

  • algorithm
  • hypertension
  • network
  • prediction
  • support vector machine

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