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. �Read more...
Abstract: 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
Content: Foreword xiii Luis Farinas 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 Pauleve, Courtney Chancellor, Maxime Folschette, Morgan Magnin and Olivier Roux Chapter 5 ASP for Construction and Validation of Regulatory Biological Networks Alexandre Rocca, Nicolas Mobilia, Eric 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 Francois 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
