The University of Edinburgh -
Division of Informatics
Forrest Hill & 80 South Bridge

MSc Thesis #9828

Title:Optimisation of Amino Acid Scoring Matrices for Improved Protein Homologue Detection
Date: 1998
Abstract:The problem of protein structure prediction remains one of the major unsolved problems in structural biochemistry. The most successful method to date for predicting protein tertiary structure from primary sequence data, is homology modelling based on alignment with similar sequences of known structure. the premier component utilised in this process is a scoring matrix which determines how similar one protein is to another.The aim of this work is to improve upon the scoring matrices currently used, in an effort to detect proteins which are more distantly related to each other. To this end an optimisation approach was taken, using a type of evolutionary algorithm. Experiments were conducted to evolve both a general scoring matrix, and a matrix which only detects a specific class of protein.The results showed that although the optimisation approach works, the matrices derived were not superior to those already in use, however they were competitive. Good results were achieved when optimising matrices to detect a particular class of protein, and this suggests that a combination of such matrices could be used as a set when performing homology searches.

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