The advances in mass spectrometry-based proteomics technologies have enabled the generation of global proteome datafrom tissue or body fluid samples collected from a broad spectrum of human diseases. Comparative proteomic analysis ofglobal proteome data identifies and prioritizes the proteins showing altered abundances, called differentially expressedproteins (DEPs), in disease samples, compared to control samples. Protein biomarker candidates that can serve as indicatorsof disease states are then selected as key molecules among these proteins. Recently, it has been addressed that cellularpathways can provide better indications of disease states than individual molecules and also network analysis of the DEPsenables effective identification of cellular pathways altered in disease conditions and key molecules representing the alteredcellular pathways. Accordingly, a number of network-based approaches to identify disease-related pathways andrepresentative molecules of such pathways have been developed. In this review, we summarize analytical platforms fornetwork-based protein biomarker discovery and key components in the platforms.
