摘要
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 hiomarkers as well as future directions to improve the methods for identifying biomarkers are also discussed.
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 hiomarkers as well as future directions to improve the methods for identifying biomarkers are also discussed.
基金
This work was partly supported by the National Nature Science Foundation of China （Nos. 91530321, 61390513, 61602347 and 61572363）, and the Fundamental Research Funds for the Central Universities.
