Title
Studying Cellular Signal Transduction with OMIC Technologies
UMMS Affiliation
Program in Systems Biology; Program in Molecular Medicine
Publication Date
2015-08-03
Document Type
Article
Disciplines
Biochemistry, Biophysics, and Structural Biology | Genetics and Genomics | Molecular Biology | Systems Biology
Abstract
In the gulf between genotype and phenotype exists proteins and, in particular, protein signal transduction systems. These systems use a relatively limited parts list to respond to a much longer list of extracellular, environmental, and/or mechanical cues with rapidity and specificity. Most signaling networks function in a highly nonlinear and often contextual manner. Furthermore, these processes occur dynamically across space and time. Because of these complexities, systems and "OMIC" approaches are essential for the study of signal transduction. One challenge in using OMIC-scale approaches to study signaling is that the "signal" can take different forms in different situations. Signals are encoded in diverse ways such as protein-protein interactions, enzyme activities, localizations, or post-translational modifications to proteins. Furthermore, in some cases signals may be encoded only in the dynamics, duration, or rates of change of these features. Accordingly, systems-level analyses of signaling may need to integrate multiple experimental and/or computational approaches. As the field has progressed, the non-triviality of integrating experimental and computational analyses has become apparent. Successful use of OMIC methods to study signaling will require the "right" experiments and the "right" modeling approaches, and it is critical to consider both in the design phase of the project. In this review, we discuss common OMIC and modeling approaches for studying signaling, emphasizing the philosophical and practical considerations for effectively merging these two types of approaches to maximize the probability of obtaining reliable and novel insights into signaling biology.
DOI of Published Version
10.1016/j.jmb.2015.07.021
Source
J Mol Biol. 2015 Aug 3. pii: S0022-2836(15)00423-4. doi: 10.1016/j.jmb.2015.07.021. [Epub ahead of print] Link to article on publisher's site
Journal/Book/Conference Title
Journal of molecular biology
Related Resources
PubMed ID
26244521
Repository Citation
Landry, Benjamin D.; Clarke, David C.; and Lee, Michael J., "Studying Cellular Signal Transduction with OMIC Technologies" (2015). Program in Systems Biology Publications and Presentations. 63.
https://escholarship.umassmed.edu/sysbio_pubs/63