Logical Modeling of Biological Systems
Systems Biology is the systematic study of the interactions between the components of a biological system and studies how these interactions give rise to the function and behavior of the living system. Through this, a life process is to be understood as a whole system rather than the collection of the parts considered separately. Systems Biology is therefore more than just an emerging field: it represents a new way of thinking about biology with a dramatic impact on the way that research is performed. The logical approach provides an intuitive method to provide explanations based on an expressive relational language.

This book covers various aspects of logical modeling of biological systems, bringing together 10 recent logic-based approaches to Systems Biology by leading scientists. The chapters cover the biological fields of gene regulatory networks, signaling networks, metabolic pathways, molecular interaction and network dynamics, and show logical methods for these domains based on propositional and first-order logic, logic programming, answer set programming, temporal logic, Boolean networks, Petri nets, process hitting, and abductive and inductive logic programming.

It provides an excellent guide for all scientists, biologists, bioinformaticians, and engineers, who are interested in logic-based modeling of biological systems, and the authors hope that new scientists will be encouraged to join this exciting scientific endeavor.

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Logical Modeling of Biological Systems
Systems Biology is the systematic study of the interactions between the components of a biological system and studies how these interactions give rise to the function and behavior of the living system. Through this, a life process is to be understood as a whole system rather than the collection of the parts considered separately. Systems Biology is therefore more than just an emerging field: it represents a new way of thinking about biology with a dramatic impact on the way that research is performed. The logical approach provides an intuitive method to provide explanations based on an expressive relational language.

This book covers various aspects of logical modeling of biological systems, bringing together 10 recent logic-based approaches to Systems Biology by leading scientists. The chapters cover the biological fields of gene regulatory networks, signaling networks, metabolic pathways, molecular interaction and network dynamics, and show logical methods for these domains based on propositional and first-order logic, logic programming, answer set programming, temporal logic, Boolean networks, Petri nets, process hitting, and abductive and inductive logic programming.

It provides an excellent guide for all scientists, biologists, bioinformaticians, and engineers, who are interested in logic-based modeling of biological systems, and the authors hope that new scientists will be encouraged to join this exciting scientific endeavor.

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Logical Modeling of Biological Systems

Logical Modeling of Biological Systems

Logical Modeling of Biological Systems

Logical Modeling of Biological Systems

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Overview

Systems Biology is the systematic study of the interactions between the components of a biological system and studies how these interactions give rise to the function and behavior of the living system. Through this, a life process is to be understood as a whole system rather than the collection of the parts considered separately. Systems Biology is therefore more than just an emerging field: it represents a new way of thinking about biology with a dramatic impact on the way that research is performed. The logical approach provides an intuitive method to provide explanations based on an expressive relational language.

This book covers various aspects of logical modeling of biological systems, bringing together 10 recent logic-based approaches to Systems Biology by leading scientists. The chapters cover the biological fields of gene regulatory networks, signaling networks, metabolic pathways, molecular interaction and network dynamics, and show logical methods for these domains based on propositional and first-order logic, logic programming, answer set programming, temporal logic, Boolean networks, Petri nets, process hitting, and abductive and inductive logic programming.

It provides an excellent guide for all scientists, biologists, bioinformaticians, and engineers, who are interested in logic-based modeling of biological systems, and the authors hope that new scientists will be encouraged to join this exciting scientific endeavor.


Product Details

ISBN-13: 9781119015215
Publisher: Wiley
Publication date: 08/08/2014
Series: ISTE
Sold by: JOHN WILEY & SONS
Format: eBook
Pages: 410
File size: 22 MB
Note: This product may take a few minutes to download.

About the Author

Luis Fariñas del Cerro, Professor, IRIT, Toulouse, France.

Katsumi Inoue, Professor, NII, Tokyo, Japan.

Table of Contents

Foreword xiii
Luis Fariñas Del Cerro

Chapter 1 Symbolic Representation and Inference or Regulatory Network Structures 1
Nataly Maimari, Krysia Broda, Antonis Kakas, Rob Krams and Alessandra Russo

Chapter 2 Reasoning on the Response of Logical Signaling Networks with ASP 49
Torsten Schaub, Anne Siegek and Santiago Videla

Chapter 3 A Logical Model for Molecular Interaction Maps 93
Robert DeMolombe, Luis Farinas Del Cerro and Naji Obeid

Chapter 4 Analyzing Large Network Dynamics with Process Hitting 125
Loic Paulevé, Courtney Chancellor, Maxime Folschette, Morgan Magnin and Olivier Roux

Chapter 5 ASP for Construction and Validation of Regulatory Biological Networks
Alexandre Rocca, Nicolas Mobilia, Éric Fanchon, Tony Ribeiro, Laurent Trilling and Katsumi Inoue

Chapter 6 Simulation-Based Reasoning about Biological Pathways Using Petri Nets and ASP 207
Saadat Anwar, Chitta Barbal and Katsumi Inoue

Chapter 7 Formal Methods Applied to Gene Networks Modeling 245
Gilles Bernot, Jean-Paul Comet and El Houssine Snaussi

Chapter 8 Temporal Logic Modeling of Dynamical Behaviors: First-Order Patterns and Solvers 291
François Fages and Pauline Traynard

Chapter 9 Analyzing SBGN-AF Networks Using Normal Logic Programs 325
Adrien Rougny, Christine Froidevaux, Yoshitaka Yamamoto and Katsumi Inoue

Chapter 10 Machine Learning of Biological Networks Using Abductive ILP 363
Alireza Tamassoni, Diahuan Lin, Hiroaki Watanabe, Jianzhong Chen and Stephen Muggleton

List of Authors 403

Index 407

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