Algorithmic Developments for Sequence Analysis, Structure Modeling and Functional Prediction of Proteins

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Title: Algorithmic Developments for Sequence Analysis, Structure Modeling and Functional Prediction of Proteins
Author: Qi, Yuan
Abstract: Sequence , structure and function , being the three most important properties of proteins , are interrelated through homology relationships . In this post -genome era , we are equipped with abundant sequence information . Homology inference is thus of great practical importance because of its ability to make structural and functional predictions through sequence analysis . In an effort to explore and utilize the protein sequence -structure -function relationships , with homology detection and utilization as the central scheme , this work concentrates on algorithmic development of methods and systems for sequence similarity search , structure modeling and functional prediction purposes , as well as performs structure prediction and classification for specific protein families . Three algorithmic developments are described in this dissertation . First , to facilitate identification of structurally or functionally important interactions between positions in a protein family , a program has been developed to perform positional correlation analysis of multiple sequence alignments using different methods . The program has been shown to be useful to identify functionally important position pairs or networks of correlated positions . Second , to further increase the sensitivity of sequence similarity search methods in terms of homology detection and structure modeling ability , a method has been developed by incorporating predicted secondary structure information with sequence profiles . Evaluation on PFAM -based system shows that this method provides improved structure template detection ability and generates alignment of better quality . Third , in order to systematically assess the structure modeling abilities of different sequence similarity search programs , a comprehensive evaluation system has been developed . This large -scale automatic evaluation system assesses the fold recognition ability and alignment quality of different programs from global and local perspectives using both reference -dependent and reference -independent approaches , which provides an instrument to understand the progress and limitations of the field . Two structure prediction and classification projects using manual analysis and existing tools are also described in this dissertation . First , the structure of C -terminal domain of Gyrase A is predicted through inferred homology relationship with regulator of chromosome condensation (RCC1 ) . This prediction has been validated by experimental data . Second , a hierarchical structure classification of thioredoxin -like fold proteins has been carried out , which promotes understanding of fold definitions and sequence -structure -function relationships
URI: http : / /hdl .handle .net /2152 .5 /602
Date: 2006-12-20


Algorithmic Developments for Sequence Analysis, Structure Modeling and Functional Prediction of Proteins. Graduate School of Biomedical Sciences. Available electronically from http : / /hdl .handle .net /2152 .5 /602 .

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