The use of internal and external functional domains to improve transmembrane protein topology prediction [electronic resource] /

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ABSTRACT Membrane proteins are involved in vital cellular functions and have important implications in disease processes, drug design and therapy. However, it is difficult to obtain diffraction quality crystals to study transmembrane protein structure. Transmembrane protein topology prediction tools try to fill in the gap between abundant number of transmembrane proteins and scarce number of known membrane protein structures (3D structure and biochemically characterized topology). However, at present, the prediction accuracy is still far from perfect. TMHMM is the current state-of- the-art method for membrane protein topology prediction. In order to improve the prediction accuracy of TMHMM, based upon the method of GenomeScan, the author implemented AHMM (augmented HMM) by incorporating functional domain information externally to TMHMM. Results show that AHMM is better than TMHMM on both helix and sidedness prediction. This improvement is verified by both statistical tests as well as sensitivity and specificity studies. It is expected that when more and more functional domain predictors are available, the prediction accuracy will be further improved. "A thesis presented to the University of Waterloo in fulfillment of the thesis requirement for the degree of Master of Mathematics in Computer Science. Thesis (M.Math)--University of Waterloo, 2004. Includes bibliographical references. Available in PDF format. System requirements: Internet connectivity and World Wide Web browser. Adobe Acrobat reader required to view and print files. Mode of access: World Wide Web.

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