Quantum physics provides the concepts and their mathematical formalization that lend themselves to describe important properties of biological networks topology, such as vulnerability to external stress and their dynamic response to changing physiological conditions. A theory of networks enhanced with mathematical concepts and tools of quantum physics opens a new area of biological physics, the one of systems biological physics.
Table of Contents
TABLE OF CONTENTS
Quantum Mechanics in Biology
The Time-independent Schrödinger Equation
Time-dependent Schrödinger Equation
Transition Probability Per Unit of Time
Quantum Coherence and Entanglement
Quantum Eﬀects in Biology
Statistical Physics in Biology
Why Statistical Physics in Biology?
The Chemical Master Equation
Chemical Master Equation and Curse of Dimensionality
Discrete Approach to Chemical Kinetics
Stochastic Simulation Algorithm
An Example of Real Enzymatic Reactions Simulated with Gillespie Algorithm
Graph Theory and Physics Meet Network Biology
Physics at the Birth of Network Biology
Mutual Information-Based Network Inference
Thermodynamics Applications in Biological Network Analysis
Electronic Physics Applications in Network Analysis
Assessment of Network Inference Methods and the Issue of Generation of Gold-Standard Data
Network Biology is Transformed by Physics
Applied Descriptors for Complexity and Centrality to Network Biology
Measures for Network Complexity and Centrality
Comparative Network Analysis
Systems Theory and Quantum Physics
Various Recapitulation Exercises
Dr. Paola Lecca is Research Scientist at the Department of Mathematics of University of Trento (Italy), and
Paola Lecca has a Master Degree in Theoretical Physics and a PhD in Computer Science and Telecommunications. She worked for several years since its foundations as researcher and principal investigator at the Microsoft Research - University of Trento, Centre for Computational and Systems Biology, where she was the leader of the research team "Knowledge inference and data management". She is currently researcher at the Department of Mathematics of University of Trento, scholarship holder at the Department of Medicine of University of Verona, and Senior Professional Member of Association for Computing Machinery. Her main research activities focus on computational modelling and algorithmic procedures implementing efficient solutions for identiafiability, controllability, and simulation of complex dynamical networks. The main applicative domains of these studies are network biology, biochemistry, biological physics, microbiology, and synthetic biology. Dr. Paola Lecca is author of about hundred publications including books and journal and conference papers on international journals in computer science, computational biology, bioinformatics, and biophysics. She carries on an intense editorial activity as editor and reviewer for high impact journals in these subjects.
Angela Re obtained her Master degree in Physics in 2004 and Ph.D. degree in 2007 in the programme – Complex Systems Applied to Post-Genomic Biology – at the University of Turin. Since then, she has been conducting an active research program in international research centres, abroad and in Italy such as the Centre for Integrative Biology in Trento and the Centre for Sustainable Future Technologies in Torino. She has a long-proven track record working with mathematical conceptualization and statistical analysis of a variety of different biological data types. Specific areas of interest include the study of eukaryotic post-transcriptional regulatory mechanisms and their inclusion in cancer and stem cell pathways as well as the application of systems and synthetic biology approaches to bacterial RNA biology, proteomics and metabolism. She contributes to develop statistical software for the analysis of network modular organization and its dynamical properties, and she is interested into integrative multi-assay genomic data visualization and integration. She is in charge of editor ad reviewer activities in peer-reviewed scientific journals.