Open AccessA survey on biomarker identification based on molecular networks
Author(s) -
Zhu Guanghui,
Zhao XingMing,
Wu Jun
Publication year - 2016
Publication title -
quantitative biology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.707
H-Index - 15
eISSN - 2095-4697
pISSN - 2095-4689
DOI - 10.1007/s40484-016-0084-z
Subject(s) - identification (biology) , biomarker , computational biology , biomarker discovery , molecular biomarkers , computer science , categorization , disease , bioinformatics , medicine , biology , proteomics , artificial intelligence , pathology , oncology , gene , genetics , botany
Background Identifying biomarkers for accurate diagnosis and prognosis of diseases is important for the prevention of disease development. The molecular networks that describe the functional relationships among molecules provide a global view of the complex biological systems. With the molecular networks, the molecular mechanisms underlying diseases can be unveiled, which helps identify biomarkers in a systematic way. Results In this survey, we report the recent progress on identifying biomarkers based on the topology of molecular networks, and we categorize those biomarkers into three groups, including node biomarkers, edge biomarkers and network biomarkers. These distinct types of biomarkers can be detected under different conditions depending on the data available. Conclusions The biomarkers identified based on molecular networks can provide more accurate diagnosis and prognosis. The pros and cons of different types of biomarkers as well as future directions to improve the methods for identifying biomarkers are also discussed.