Network biomarkers, interaction networks and dynamical network biomarkers in respiratory diseases

Abstract Identification and validation of interaction networks and network biomarkers have become more critical and important in the development of disease‐specific biomarkers, which are functionally changed during disease development, progression or treatment. The present review headlined the defin...

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Main Authors: Xiaodan Wu, Luonan Chen, Xiangdong Wang
Format: Article
Language:English
Published: Wiley 2014-12-01
Series:Clinical and Translational Medicine
Subjects:
Online Access:https://doi.org/10.1186/2001-1326-3-16
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spelling doaj-85da8d523b4d48a7aa8dd2c6542ec36b2020-11-25T03:36:23ZengWileyClinical and Translational Medicine2001-13262014-12-0131n/an/a10.1186/2001-1326-3-16Network biomarkers, interaction networks and dynamical network biomarkers in respiratory diseasesXiaodan Wu0Luonan Chen1Xiangdong Wang2Department of Respiratory MedicineZhongshan HospitalFudan UniversityShanghaiChinaKey Laboratory of Systems BiologySIBS‐Novo Nordisk PreDiabetes CenterShanghai Institutes for Biological SciencesChinese Academy of SciencesShanghaiChinaDepartment of Respiratory MedicineZhongshan HospitalFudan UniversityShanghaiChinaAbstract Identification and validation of interaction networks and network biomarkers have become more critical and important in the development of disease‐specific biomarkers, which are functionally changed during disease development, progression or treatment. The present review headlined the definition, significance, research and potential application for network biomarkers, interaction networks and dynamical network biomarkers (DNB). Disease‐specific interaction networks, network biomarkers, or DNB have great significance in the understanding of molecular pathogenesis, risk assessment, disease classification and monitoring, or evaluations of therapeutic responses and toxicities. Protein‐based DNB will provide more information to define the differences between the normal and pre‐disease stages, which might point to early diagnosis for patients. Clinical bioinformatics should be a key approach to the identification and validation of disease‐specific biomarkers.https://doi.org/10.1186/2001-1326-3-16Network biomarkersDynamic network biomarkersLung cancerDiagnosisPrognosis
collection DOAJ
language English
format Article
sources DOAJ
author Xiaodan Wu
Luonan Chen
Xiangdong Wang
spellingShingle Xiaodan Wu
Luonan Chen
Xiangdong Wang
Network biomarkers, interaction networks and dynamical network biomarkers in respiratory diseases
Clinical and Translational Medicine
Network biomarkers
Dynamic network biomarkers
Lung cancer
Diagnosis
Prognosis
author_facet Xiaodan Wu
Luonan Chen
Xiangdong Wang
author_sort Xiaodan Wu
title Network biomarkers, interaction networks and dynamical network biomarkers in respiratory diseases
title_short Network biomarkers, interaction networks and dynamical network biomarkers in respiratory diseases
title_full Network biomarkers, interaction networks and dynamical network biomarkers in respiratory diseases
title_fullStr Network biomarkers, interaction networks and dynamical network biomarkers in respiratory diseases
title_full_unstemmed Network biomarkers, interaction networks and dynamical network biomarkers in respiratory diseases
title_sort network biomarkers, interaction networks and dynamical network biomarkers in respiratory diseases
publisher Wiley
series Clinical and Translational Medicine
issn 2001-1326
publishDate 2014-12-01
description Abstract Identification and validation of interaction networks and network biomarkers have become more critical and important in the development of disease‐specific biomarkers, which are functionally changed during disease development, progression or treatment. The present review headlined the definition, significance, research and potential application for network biomarkers, interaction networks and dynamical network biomarkers (DNB). Disease‐specific interaction networks, network biomarkers, or DNB have great significance in the understanding of molecular pathogenesis, risk assessment, disease classification and monitoring, or evaluations of therapeutic responses and toxicities. Protein‐based DNB will provide more information to define the differences between the normal and pre‐disease stages, which might point to early diagnosis for patients. Clinical bioinformatics should be a key approach to the identification and validation of disease‐specific biomarkers.
topic Network biomarkers
Dynamic network biomarkers
Lung cancer
Diagnosis
Prognosis
url https://doi.org/10.1186/2001-1326-3-16
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AT luonanchen networkbiomarkersinteractionnetworksanddynamicalnetworkbiomarkersinrespiratorydiseases
AT xiangdongwang networkbiomarkersinteractionnetworksanddynamicalnetworkbiomarkersinrespiratorydiseases
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