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Old Dominion University

Biological Networks: Modeling and Structural Analysis

Abstract

dc:description.abstract

<p>Biological networks are receiving increased attention due to their importance in understanding life at the cellular level. There exist many different kinds of biological networks, and different models have been proposed for them. In this dissertation we focus on suitable network models for representing experimental data on protein interaction networks and protein complex networks (protein complexes are groups of proteins that associate to accomplish some function in the cell), and to design algorithms for exploring such networks. Our goal is to enable biologists to identify the general principles that govern the organization of protein-protein interaction networks and protein complex networks. For protein complex networks, we propose a hypergraph model which more accurately represents the data than earlier models. We define the concept of <em>k</em>-cores in hypergraphs, which are highly connected subhypergraphs, and design an algorithm for computing <em>k </em>-cores in hypergraphs. A major challenge in computational systems biology is to understand the modular structure of biological networks. We construct computational models for predicting functional modules through the use of graph clustering techniques. The application of earlier graph clustering techniques to proteomic networks does not yield good results due to the high error rates present, and the small-world and power-law properties of these networks. We discuss the various requirements that clusterings of biological networks are required to satisfy, design an algorithm for computing a clustering, and show that our clustering approach is robust and scalable. Moreover, we design a new algorithm to compute overlapping clustering rather than exclusive clustering. Our approach identifies a set of clusters and a set of bridge proteins that form the overlap among the clusters. Finally we assess the quality of our proposed clusterings using different reference sets.</p>

Degree

thesis:*
Name thesis:degree_name
Doctor of Philosophy (PhD)
Level thesis:degree_level
Dissertation
Discipline thesis:degree_discipline
Computer Science
Year dc:date.available
2008

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Ramadan, Emad Y.
Contributors dc:contributor
  • Alex Pothen
  • Kurt Maly
  • Mohammad Zubair
  • Jessica Crouch
  • Christopher Osgood

Subjects

dc:subject × 5

Rights

dc:rights
Statement dc:rights
  • <p>In Copyright. URI: <a href="http://rightsstatements.org/vocab/InC/1.0/">http://rightsstatements.org/vocab/InC/1.0/</a> This Item is protected by copyright and/or related rights. You are free to use this Item in any way that is permitted by the copyright and related rights legislation that applies to your use. For other uses you need to obtain permission from the rights-holder(s).</p>

Identifiers

dc:identifier.*
Identifier
9780549928546
OAI identifier oai:identifier
oai:digitalcommons.odu.edu:computerscience_etds-1061

Chain of custody

source
Harvested from
Old Dominion University
Base URL
digitalcommons.odu.edu/do/oai/
Last updated
2026-07-24
Source record
OAI-PMH GetRecord
citation

Ramadan, Emad Y.. Biological Networks: Modeling and Structural Analysis. Dissertation thesis, 2008. https://digitalcommons.odu.edu/computerscience_etds/61