Modeling in Computational Biology and Biomedicine

Computational biology, mathematical biology, biology and biomedicine are currently undergoing spectacular progresses due to a synergy between technological advances and inputs from physics, chemistry, mathematics, statistics and computer science. The goal of this book is to evidence this synergy by describing selected developments in the following fields: bioinformatics, biomedicine and neuroscience.

This work is unique in two respects - first, by the variety and scales of systems studied and second, by its presentation: Each chapter provides the biological or medical context, follows up with mathematical or algorithmic developments triggered by a specific problem and concludes with one or two success stories, namely new insights gained thanks to these methodological developments. It also highlights some unsolved and outstanding theoretical questions, with a potentially high impact on these disciplines.  

Two communities will be particularly interested in this book. The first one is the vast community of applied mathematicians and computer scientists, whose interests should be captured by the added value generated by the application of advanced concepts and algorithms to challenging biological or medical problems. The second is the equally vast community of biologists. Whether scientists or engineers, they will find in this book a clear and self-contained account of concepts and techniques from mathematics and computer science, together with success stories on their favorite systems. The variety of systems described represents a panoply of complementary conceptual tools. On a practical level, the resources listed at the end of each chapter (databases, software) offer invaluable support for getting started on a specific topic in the fields of biomedicine, bioinformatics and neuroscience.

Frédéric Cazals holds a PhD in Theoretical Computer Science from the University of Paris VII. He is Research Director at INRIA Sophia-Antipolis Méditerranée, where he leads the Algorithms-Biology-Structure project-team. His research interests span geometric and topological modeling, scientific software development, and computational structural biology.

Pierre Kornprobst holds a PhD in Mathematics from the University of Nice Sophia Antipolis. He is a researcher at INRIA Sophia-Antipolis Méditerranée. His research interest is the study of vision, from computational and biological perspectives, including image processing using partial differential equations, retina modeling, motion perception estimation and categorization.