Research@StAndrews
 
The University of St Andrews

Research@StAndrews:FullText >
Biology (School of) >
Biology >
Biology Theses >

Please use this identifier to cite or link to this item: http://hdl.handle.net/10023/3119
This item has been viewed 17 times in the last year. View Statistics

Files in This Item:

File Description SizeFormat
Thefulltextofthisdocumentisnotavailable.pdfThesis4.23 kBAdobe PDFView/Open
Title: An investigation of human protein interactions using the comparative method
Authors: Ur-Rehman, Saif
Supervisors: Barker, Daniel
Keywords: Phylogenetic profiling
Comparative method
Dollo parsimony
Eukaryotic phylogeny
Human protein-protein interactions
Ortholog detection
Ancestral content reconstruction
Bioinformatics
Correlated gain and loss
Issue Date: 20-Jun-2012
Abstract: There is currently a large increase in the speed of production of DNA sequence data as next generation sequencing technologies become more widespread. As such there is a need for rapid computational techniques to functionally annotate data as it is generated. One computational method for the functional annotation of protein-coding genes is via detection of interaction partners. If the putative partner has a functional annotation then this annotation can be extended to the initial protein via the established principle of “guilt by association”. This work presents a method for rapid detection of functional interaction partners for proteins through the use of the comparative method. Functional links are sought between proteins through analysis of their patterns of presence and absence amongst a set of 54 eukaryotic organisms. These links can be either direct or indirect protein interactions. These patterns are analysed in the context of a phylogenetic tree. The method used is a heuristic combination of an established accurate methodology involving comparison of models of evolution the parameters of which are estimated using maximum likelihood, with a novel technique involving the reconstruction of ancestral states using Dollo parsimony and analysis of these reconstructions through the use of logistic regression. The methodology achieves comparable specificity to the use of gene coexpression as a means to predict functional linkage between proteins. The application of this method permitted a genome-wide analysis of the human genome, which would have otherwise demanded a potentially prohibitive amount of computational resource. Proteins within the human genome were clustered into orthologous groups. 10 of these proteins, which were ubiquitous across all 54 eukaryotes, were used to reconstruct a phylogeny. An application of the heuristic predicted a set of functional protein interactions in human cells. 1,142 functional interactions were predicted. Of these predictions 1,131 were not present in current protein-protein interaction databases.
URI: http://hdl.handle.net/10023/3119
Type: Thesis
Publisher: University of St Andrews
Appears in Collections:Biology Theses



This item is protected by original copyright

This item is licensed under a Creative Commons License
Creative Commons

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.

 

DSpace Software Copyright © 2002-2012  Duraspace - Feedback
For help contact: Digital-Repository@st-andrews.ac.uk | Copyright for this page belongs to St Andrews University Library | Terms and Conditions (Cookies)