Comparative Analysis of Biological Networks | Algorithmic and Analytical Methods for Cross-Species Analysis of Biomolecular Interactions

Mehmet Koyutürk

ISBN 10: 3639110358 / ISBN 13: 9783639110357

Published by VDM Verlag Dr. Müller, 2009

About this Item

Comparative Analysis of Biological Networks | Algorithmic and Analytical Methods for Cross-Species Analysis of Biomolecular Interactions | Mehmet Koyutürk | Taschenbuch | Englisch | VDM Verlag Dr. Müller | EAN 9783639110357 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.

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Bibliographic Details

• Title: Comparative Analysis of Biological Networks | Algorithmic and Analytical Methods for Cross-Species Analysis of Biomolecular Interactions
• Publisher: VDM Verlag Dr. Müller
• Publication Date: 2009
• Language: English
• ISBN 10: 3639110358
• ISBN 13: 9783639110357
• Binding: Taschenbuch
• Condition: Neu
• Dimensions: 220W x 150H x 7D millimeters 220 millimeters width by 150 millimeters height by 7 millimeters depth
• Weight: 197 grams
• Seller catalogs:
  • Bücher

About this title

Synopsis

Recent developments in molecular biology have resulted in experimental data that entails the relationships and interactions between biomolecules. Biomolecular interaction data, generally referred to as biological or cellular networks, are frequently abstracted using graph models. In systems biology, comparative analysis of these networks provides understanding of functional modularity in the cell by integrating cellular organization, functional hierarchy, and evolutionary conservation. In this study, we address a number of algorithmic issues associated with comparative analysis of molecular interaction networks. We first discuss the problem of identifying common sub-networks in a collection of molecular interaction networks belonging to diverse species. With a view to understanding the conservation and divergence of functional modules, we also develop network alignment techniques, grounded in theoretical models of network evolution. Finally, we probabilistically analyze the existence of highly connected and conserved subgraphs in random graphs, in order to assess the statistical significance of the patterns identified by our algorithms.

About the Author

Mehmet Koyutürk received his M.S. degree in Computer Engineering (1998) and Ph.D. degree Computer Science (2006), respectively from Bilkent University and Purdue University. In 2007, he joined the Electrical Engineering & Computer Science Department of Case Western Reserve University as T. & D. Schroeder Assistant Professor.