An Omnidirectional Visualization Model of Personalized Gene Regulatory Networks

Overview

Journal NPJ Syst Biol Appl

Specialty Biology

Date 2019 Oct 22

PMID 31632690

Citations 10

Authors

Chixiang Chen

Libo Jiang

Guifang Fu

Ming Wang

Yaqun Wang

Biyi Shen

Zhenqiu Liu

Zuoheng Wang

Wei Hou

Scott A Berceli

Rongling Wu

Affiliations

Soon will be listed here.

Abstract

Gene regulatory networks (GRNs) have been widely used as a fundamental tool to reveal the genomic mechanisms that underlie the individual's response to environmental and developmental cues. Standard approaches infer GRNs as holistic graphs of gene co-expression, but such graphs cannot quantify how gene-gene interactions vary among individuals and how they alter structurally across spatiotemporal gradients. Here, we develop a general framework for inferring informative, dynamic, omnidirectional, and personalized networks (idopNetworks) from routine transcriptional experiments. This framework is constructed by a system of quasi-dynamic ordinary differential equations (qdODEs) derived from the combination of ecological and evolutionary theories. We reconstruct idopNetworks using genomic data from a surgical experiment and illustrate how network structure is associated with surgical response to infrainguinal vein bypass grafting and the outcome of grafting. idopNetworks may shed light on genotype-phenotype relationships and provide valuable information for personalized medicine.

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