Abstract
Protein domain identification and analysis are cornerstones of modern proteomics. The tools available to protein domain researchers avail a variety of approaches to understanding large protein domain families. Hidden Markov Models (HMM) form the basis for identifying and categorizing evolutionarily linked protein domains. Here I describe the use of HMM models for predicting and identifying Src Homology 2 (SH2) domains within the proteome.
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Acknowledgments
The knowledge amassed to write this chapter was based on work supported by the University of Chicago Cancer Research Foundation Women’s Board and Piers Nash’s laboratory at the University of Chicago Ben May Department for Cancer Research.
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Jablonowski, K. (2017). Hidden Markov Models for Protein Domain Homology Identification and Analysis. In: Machida, K., Liu, B. (eds) SH2 Domains. Methods in Molecular Biology, vol 1555. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-6762-9_3
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DOI: https://doi.org/10.1007/978-1-4939-6762-9_3
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