Applications of systems approaches in the study of rheumatic diseases.
10.3904/kjim.2015.30.2.148
- Author:
Ki Jo KIM
1
;
Saseong LEE
;
Wan Uk KIM
Author Information
1. Division of Rheumatology, Department of Internal Medicine, St. Vincent's Hospital, College of Medicine, The Catholic University of Korea, Suwon, Korea.
- Publication Type:Review ; Research Support, Non-U.S. Gov't
- Keywords:
Systems biology;
Network analysis;
Rheumatic diseases
- MeSH:
Animals;
Antirheumatic Agents/therapeutic use;
Biomedical Research/*methods;
Cytokines/genetics/metabolism;
Genetic Markers;
Genetic Predisposition to Disease;
Humans;
Inflammation Mediators/metabolism;
Molecular Targeted Therapy;
Phenotype;
Prognosis;
*Rheumatic Diseases/drug therapy/genetics/metabolism/physiopathology;
Rheumatology/*methods;
Risk Factors;
Signal Transduction;
*Systems Biology;
Systems Integration
- From:The Korean Journal of Internal Medicine
2015;30(2):148-160
- CountryRepublic of Korea
- Language:English
-
Abstract:
The complex interaction of molecules within a biological system constitutes a functional module. These modules are then acted upon by both internal and external factors, such as genetic and environmental stresses, which under certain conditions can manifest as complex disease phenotypes. Recent advances in high-throughput biological analyses, in combination with improved computational methods for data enrichment, functional annotation, and network visualization, have enabled a much deeper understanding of the mechanisms underlying important biological processes by identifying functional modules that are temporally and spatially perturbed in the context of disease development. Systems biology approaches such as these have produced compelling observations that would be impossible to replicate using classical methodologies, with greater insights expected as both the technology and methods improve in the coming years. Here, we examine the use of systems biology and network analysis in the study of a wide range of rheumatic diseases to better understand the underlying molecular and clinical features.
