A Comparative Study on Biological Networks | Mining biological networks for similar patterns through network alignment and analysis of network dynamics

Ferhat Ay

ISBN 10: 3844394664 / ISBN 13: 9783844394665

Published by LAP LAMBERT Academic Publishing, 2013

About this Item

A Comparative Study on Biological Networks | Mining biological networks for similar patterns through network alignment and analysis of network dynamics | Ferhat Ay | Taschenbuch | 216 S. | Englisch | 2013 | LAP LAMBERT Academic Publishing | EAN 9783844394665 | Verantwortliche Person für die EU: BoD - Books on Demand, In de Tarpen 42, 22848 Norderstedt, info[at]bod[dot]de | Anbieter: preigu.

Seller Inventory # 106956626

Bibliographic Details

• Title: A Comparative Study on Biological Networks | Mining biological networks for similar patterns through network alignment and analysis of network dynamics
• Publisher: LAP LAMBERT Academic Publishing
• Publication Date: 2013
• Language: English
• ISBN 10: 3844394664
• ISBN 13: 9783844394665
• Binding: Taschenbuch
• Condition: Neu
• Dimensions: 220W x 150H x 13D millimeters 220 millimeters width by 150 millimeters height by 13 millimeters depth
• Weight: 340 grams
• Seller catalogs:
  • Bücher

About this title

Synopsis

Biological networks encapsulate invaluable information about the roles of different entities and their interactions with each other. Analyzing these networks is essential to reveal evolutionary differences between different cells and organisms. An important type of analysis is the comparative analysis which aims at identifying functionally similar components of these networks. Analogous to sequence alignment which identifies sequence similarity, network alignment reveals similar connectivity patterns such as alternative paths and subnetworks. Additional to the comparative analysis, examining solely the topological structure led to discovery of the steady states and the modular organization that these networks exhibit. This book introduces (i) Alignment algorithms for metabolic networks that account for heterogeneous network elements, connected subnetwork mappings and the scalability problem; (ii) An algorithm that predicts functional similarity between reactions based on metabolic flux analysis; (iii) Efficient methods that identify steady states of Boolean regulatory networks; (iv) An algorithm that identifies dynamic modular structure of regulatory networks.

About the Author

Ferhat Ay received his PhD degree from Computer Science at University of Florida in 2011. He received his B.S. degrees from Computer Engineering and Mathematics both from Middle East Technical University (METU), Turkey in 2007. His research focuses on developing algorithms for alignment and topological analysis of various biological networks.