Abstract

Protein sequence analysis tools to predict homology, structure, and function of particular peptide sequences exist in abundance. One of the most commonly used tools is the profile hidden Markov model algorithm developed by Eddy and co-workers [1, 2]. These tools allow scientists to construct mathematical models (hidden Markov models or HMM) of a set of aligned protein sequences with known similar function and homology, which is then applicable to a large database of proteins. The tools provide the ability to generate a log-odds score as to whether or not the protein belongs to the same family as the proteins that generated the HMM or to a set of random unrelated sequences.
Due to the complexity of the calculation and the possibility to apply many HMMs to a single sequence (Pfam search), these calculations require significant numbers of processing cycles. Efforts to accelerate these searches have resulted …

Date

October 10, 2025

Authors

John Paul Walters, Joseph Landman, Vipin Chaudhary

Book

Grid computing for bioinformatics and computational biology

Pages

51-70

Publisher

John Wiley & Sons, Inc.