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 |
|
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 |
|
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 |
|
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 |
|
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 |
|
6.9.Online Resources |
|
Part III Modeling in neuroscience |
|
7.Single-Trial Analysis of Bioelectromagnetic Signals: The Quest for Hidden Information. M.Clerc, T.Papadopoulo, and C.Bénar |
|
7.1.Introduction |
|
7.2.Data-driven Approaches: Non-linear Dimensionality Reduction |
|
7.3.Model-Driven Approaches: Matching Pursuit and its Extensions |
|
7.4.Success Stories |
|
7.5.Conclusion |
|
7.6.Selected Online Resources |
|
8 Spike Train Statistics from Empirical Facts to Theory: The Case of the Retina. B.Cessac and A.Palacios |
|
8.1.Introduction |
|
8.2.Unraveling the Neural Code in the Retina via Spike Train Statistics Analysis |
|
8.3.Spike Train Statistics from a Theoretical Perspective |
|
8.4.Using Gibbs Distributions to Analysing Spike Trains Statistics |
|
8.5.Conclusion |
|
8.6.Outlook |
|
8.7.Online Resources |
|
Biology, Medicine and Biophysics |
|
Mathematics and Computer Science |
|
Index |
|
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 |
|