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E-raamat: Evolutionary Computation in Gene Regulatory Network Research

Edited by (University of Tokyo, Tokyo, Japan), Series edited by (University of Western Australia), Edited by (University of Newcastle, NSW, Australia), Series edited by (Department of Computer Science, Georgia State University)
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Introducing a handbook for gene regulatory network research using evolutionary computation, with applications for computer scientists, computational and system biologists

This book is a step-by-step guideline for research in gene regulatory networks (GRN) using evolutionary computation (EC). The book is organized into four parts that deliver materials in a way equally attractive for a reader with training in computation or biology. Each of these sections, authored by well-known researchers and experienced practitioners, provides the relevant materials for the interested readers. The first part of this book contains an introductory background to the field. The second part presents the EC approaches for analysis and reconstruction of GRN from gene expression data. The third part of this book covers the contemporary advancements in the automatic construction of gene regulatory and reaction networks and gives direction and guidelines for future research. Finally, the last part of this book focuses on applications of GRNs with EC in other fields, such as design, engineering and robotics.

Provides a reference for current and future research in gene regulatory networks (GRN) using evolutionary computation (EC)

Covers sub-domains of GRN research using EC, such as expression profile analysis, reverse engineering, GRN evolution, applications

Contains useful contents for courses in gene regulatory networks, systems biology, computational biology, and synthetic biology

Delivers state-of-the-art research in genetic algorithms, genetic programming, and swarm intelligence

Evolutionary Computation in Gene Regulatory Network Research is a reference for researchers and professionals in computer science, systems biology, and bioinformatics, as well as upper undergraduate, graduate, and postgraduate students.

Hitoshi Iba is a Professor in the Department of Information and Communication Engineering, Graduate School of Information Science and Technology, at the University of Tokyo, Toyko, Japan. He is an Associate Editor of the IEEE Transactions on Evolutionary Computation and the journal of Genetic Programming and Evolvable Machines.   Nasimul Noman is a lecturer in the School of Electrical Engineering and Computer Science at the University of Newcastle, NSW, Australia. From 2002 to 2012 he was a faculty member at the University of Dhaka, Bangladesh. Noman is an Editor of the BioMed Research International journal. His research interests include computational biology, synthetic biology, and bioinformatics.
Preface ix
Acknowledgments xiii
Contributors xv
I Preliminaries
1 A Brief Introduction to Evolutionary and other Nature-Inspired Algorithms
3(27)
Nasimul Noman
Hitoshi Iba
2 Mathematical Models and Computational Methods for Inference of Genetic Networks
30(19)
Tatsuya Akutsu
3 Gene Regulatory Networks: Real Data Sources and Their Analysis
49(20)
Yuji Zhang
II EAs For Gene Expression Data Analysis And GRN Reconstruction
4 Biclustering Analysis of Gene Expression Data Using Evolutionary Algorithms
69(27)
Alan Wee-Chung Liew
5 Inference of Vohradsky's Models of Genetic Networks Using a Real-Coded Genetic Algorithm
96(22)
Shuhei Kimura
6 GPU-Powered Evolutionary Design of Mass-Action-Based Models of Gene Regulation
118(33)
Marco S. Nobile
Davide Cipolla
Paolo Cazzaniga
Daniela Besozzi
7 Modeling Dynamic Gene Expression in Streptomyces Coelicolor: Comparing Single and Multi-Objective Setups
151(34)
Spencer Angus Thomas
Yaochu Jin
Emma Laing
Colin Smith
8 Reconstruction of Large-Scale Gene Regulatory Network Using S-system Model
185(28)
Ahsan Raja Chowdhury
Madhu Chetty
III EAs For Evolving GRNs And Reaction Networks
9 Design Automation of Nucleic Acid Reaction System Simulated by Chemical Kinetics Based on Graph Rewriting Model
213(27)
Ibuki Kawamata
Masami Hagiya
10 Using Evolutionary Algorithms to Study the Evolution of Gene Regulatory Networks Controlling Biological Development
240(29)
Alexander Spirov
David Holloway
11 Evolving GRN-inspired In Vitro Oscillatory Systems
269(32)
Quang Huy Dinh
Nathanael Aubert
Nasimul Noman
Hitoshi Iba
Yannic Rondelez
IV Application Of GRN With EAs
12 Artificial Gene Regulatory Networks for Agent Control
301(26)
Sylvain Cussat-Blanc
Jean Disset
Stephane Sanchez
Yves Duthen
13 Evolving H-GRNs for Morphogenetic Adaptive Pattern Formation of Swarm Robots
327(35)
Hyondong Oh
Yaochu Jin
14 Regulatory Representations in Architectural Design
362(36)
Daniel Richards
Martyn Amos
15 Computing with Artificial Gene Regulatory Networks
398(27)
Michael A. Lones
Index 425
Hitoshi Iba is a Professor in the Department of Information and Communication Engineering, Graduate School of Information Science and Technology, at the University of Tokyo, Tokyo, Japan. He is an Associate Editor of the IEEE Transactions on Evolutionary Computation and the Journal of Genetic Programming and Evolvable Machines.

Nasimul Noman is a Lecturer in the School of Electrical Engineering and Computer Science at the University of Newcastle, NSW, Australia. From 2002 to 2012, he was a faculty member at the University of Dhaka, Bangladesh. Noman is an Editor of the BioMed Research International journal. His research interests include computational biology, synthetic biology, and bioinformatics.