Àá½Ã¸¸ ±â´Ù·Á ÁÖ¼¼¿ä. ·ÎµùÁßÀÔ´Ï´Ù.
KMID : 1132720160140010002
Genomics & Informatics
2016 Volume.14 No. 1 p.2 ~ p.11
Network-Based Protein Biomarker Discovery Platforms
Kim Min-Hyung

Hwang Dae-Hee
Abstract
The advances in mass spectrometry-based proteomics technologies have enabled the generation of global proteome data from tissue or body fluid samples collected from a broad spectrum of human diseases. Comparative proteomic analysis of global proteome data identifies and prioritizes the proteins showing altered abundances, called differentially expressed proteins (DEPs), in disease samples, compared to control samples. Protein biomarker candidates that can serve as indicators of disease states are then selected as key molecules among these proteins. Recently, it has been addressed that cellular pathways can provide better indications of disease states than individual molecules and also network analysis of the DEPs enables effective identification of cellular pathways altered in disease conditions and key molecules representing the altered cellular pathways. Accordingly, a number of network-based approaches to identify disease-related pathways and representative molecules of such pathways have been developed. In this review, we summarize analytical platforms for network-based protein biomarker discovery and key components in the platforms.
KEYWORD
biomarkers, LC-MS/MS, network analysis, proteomics
FullTexts / Linksout information
Listed journal information
ÇмúÁøÈïÀç´Ü(KCI) KoreaMed