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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Online Access: | https://doi.org/10.1186/2001-1326-3-16 |
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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 |
work_keys_str_mv |
AT xiaodanwu networkbiomarkersinteractionnetworksanddynamicalnetworkbiomarkersinrespiratorydiseases AT luonanchen networkbiomarkersinteractionnetworksanddynamicalnetworkbiomarkersinrespiratorydiseases AT xiangdongwang networkbiomarkersinteractionnetworksanddynamicalnetworkbiomarkersinrespiratorydiseases |
_version_ |
1724550177308540928 |