Modeling in Computational Biology and Biomedicine

Foreword by Olivier Faugeras.- Foreword by Joël Janin.- Preface.- Part I Bioinformatics.- 1.Modeling Macro-molecular Complexes: a Journey Across Scales. F.Cazals, T.Dreyfus, and C.H. Robert.- 1.1.Introduction.- 1.2.Modeling Atomic Resolution.- 1.3.Modeling Large Assemblies.- 1.4.Outlook.- 1.5.Online Resources.- References.- 2.Modeling and Analysis of Gene Regulatory Networks. G.Bernot, J-P.Comet, A.Richard, M.Chaves, J-L.Gouzé, and F.Dayan.- 2.1.Introduction.- 2.2.Continuous and Hybrid Models of Genetic Regulatory Networks.- 2.3.Discrete Models of GRN.- 2.4.Outlook.- 2.5.Online Resources.- 2.6.Acknowledgments.- References.- Part II Biomedical Signal and Image Analysis.- 3.Noninvasive Cardiac Signal Analysis Using Data Decomposition Techniques. V.Zarzoso, O.Meste, P.Comon, D.G.Latcu, and N.Saoudi.- 3.1.Preliminaries and Motivation.- 3.2.T-Wave Alternans Detection via Principal Component Analysis.- 3.3.Atrial Activity Extraction via Independent Component Analysis.- 3.4.Conclusion and Outlook.- 3.5.Online Resources.- References.- 4.Deconvolution and Denoising for Confocal Microscopy. P.Pankajakshan, G.Engler, L.Blanc-Féraud, and J.Zerubia.- 4.1.Introduction.- 4.2.Development of the Auxiliary Computational Lens.- 4.3.Outlook.- 4.4.Selected Online Resources.- References.- 5.Statistical Shape Analysis of Surfaces in Medical Images Applied to the Tetralogy of Fallot Heart. K.McLeod, T.Mansi, M.Sermesant, G.Pongiglione, and X.Pennec.- 5.1.Introduction.- 5.2.Statistical Shape Analysis.- 5.3.Shape Analysis of ToF Data.- 5.4.Conclusion.- 5.5.Online Resources.- References.- 6.From Diffusion MRI to Brain Connectomics. A.Ghosh and R.Deriche.- 6.1.Introduction.- 6.2.A Brief History of NMR and MRI.- 6.3.Nuclear Magnetic Resonance and Diffusion.- 6.4.From Diffusion MRI to Tissue Microstructure.- 6.5.Computational Framework for Processing Diffusion MR Images.- 6.6.Tractography: Inferring the Connectivity.- 6.7.Clinical Applications 6.8.Conclusion.-

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.

From the reviews:"'A principal goal of this book is to illustrate that in modeling biological systems, deeper insights can be gained using more advanced mathematical and algorithmic developments that implicate a wide spectrum of techniques from applied mathematics and computer science.' The book achieves this goal. ... this is a well-organized and well-written book, with timely information for multidisciplinary researchers in the bioinformatics, biomedical signal and image analysis, and neuroscience modeling fields." (Jindong Liu, Computing Reviews, April, 2013)