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Updated: Jul 13, 2026

JUMPn: A Streamlined Application for Protein Co-Expression Clustering and Network Analysis in Proteomics
Published on: October 19, 2021
Advancing signaling networks through proteomics
Tina L Tekirian1, Stefani N Thomas, Austin Yang
1University of Maryland School of Medicine, Greenebaum Cancer Center, Baltimore, MD 21201, USA. ttekirian@som.umaryland.edu
Abstract:
Healthful physiology can be distinguished from unhealthful physiology by focusing upon how a given signal transduction pathway is shifted as a function of disease. In order to distinguish between pathways that contribute to normal versus disease biology, it is necessary to identify components that comprise a protein module. The development of methods that target such differences is essential for the identification, development and validation of biomarkers that can improve the quality of diagnoses and treatment of disease. This review discusses the use of proteomic methods that integrate cell biology, mass spectrometry and bioinformatics, in relation to the analyses of protein signaling modules that are subject to differential phosphorylation. We examine how these methods can be used to distinguish abnormal from normal physiology.
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