Computational Systems Biology

Computational Systems Biology: Inference and Modelling provides an introduction to, and overview of, network analysis inference approaches which form the backbone of the model of the complex behavior of biological systems.

This book addresses the challenge to integrate highly diverse quantitative approaches into a unified framework by highlighting the relationships existing among network analysis, inference, and modeling.

The chapters are light in jargon and technical detail so as to make them accessible to the non-specialist reader. The book is addressed at the heterogeneous public of modelers, biologists, and computer scientists.

• Provides a unified presentation of network inference, analysis, and modeling
• Explores the connection between math and systems biology, providing a framework to learn to analyze, infer, simulate, and modulate the behavior of complex biological systems
• Includes chapters in modular format for learning the basics quickly and in the context of questions posed by systems biology
• Offers a direct style and flexible formalism all through the exposition of mathematical concepts and biological applications

Auteur

Paola Lecca received a M.S. in Theoretical Physics from the University of Trento (Italy) in 1997 and a PhD in Computer Science in 2006 from the International Doctorate School in Information and Communication Technologies at the University of Trento (Italy). Since 1998 she held Researcher and Principal Investigator positions in research centers and in academia. From 1998 to 2000 she was Research Assistant at the Fondazione Bruno Kessler - Center for Information Technologies of Trento by the research unit of Predictive Models for Biomedicine & Environment. From 2001 to 2002 Dr. Lecca worked at the Department of Physics of University of Trento in the area of data manipulation and predictive modelling in research programs of the National Institute of Nuclear Physics. In 2006 she joined to The Microsoft-Research University of Trento Centre for Computational and Systems Biology (COSBI), Italy. At COSBI Dr. Lecca led the group of Data Manipulation and Knowledge Inference. From 2012 to 2015 Dr. Lecca continued her researches at the Laboratory of Computational Oncology of the Centre for Integrative Biology (CIBIO) of University of Trento, Italy. She is currently collaborating with the Department of Mathematics of University of Trento, where she develops optimized techniques of simulation of hybrid (stochastic and deterministic) dynamical biochemical systems.She is a Professional Member of Association for Computing Machinery and author of seventy publications including books and journal and conference papers on international journals in computational biology, bioinformatics, and biophysics. She carries on an intense editorial activity as editor and reviewer for high impact factor journals in these subjects, and leads the organization of school and symposia of bioinformatics.

Contenu

Chapter 1: Overview of Biological Network Inference and Modeling of Dynamics

Chapter 2: Network Inference From Steady-State Data

Chapter 3: Network Inference From Time-Course Data

Chapter 4: Network-Based Conceptualization of Observational Data

Chapter 5: Deterministic Differential Equations

Chapter 6: Stochastic Differential Equations

Chapter 7: From Network Inference to the Study of Human Diseases

Chapter 8: Conclusions