Ivo F. Sbalzarini
Max Planck Society
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Featured researches published by Ivo F. Sbalzarini.
Nature Methods | 2014
Nicolas Chenouard; Ihor Smal; Fabrice de Chaumont; Martin Maška; Ivo F. Sbalzarini; Yuanhao Gong; Janick Cardinale; Craig Carthel; Stefano Coraluppi; Mark R. Winter; Andrew R. Cohen; William J. Godinez; Karl Rohr; Yannis Kalaidzidis; Liang Liang; James Duncan; Hongying Shen; Yingke Xu; Klas E. G. Magnusson; Joakim Jaldén; Helen M. Blau; Perrine Paul-Gilloteaux; Philippe Roudot; Charles Kervrann; François Waharte; Jean-Yves Tinevez; Spencer Shorte; Joost Willemse; Katherine Celler; Gilles P. van Wezel
Particle tracking is of key importance for quantitative analysis of intracellular dynamic processes from time-lapse microscopy image data. Because manually detecting and following large numbers of individual particles is not feasible, automated computational methods have been developed for these tasks by many groups. Aiming to perform an objective comparison of methods, we gathered the community and organized an open competition in which participating teams applied their own methods independently to a commonly defined data set including diverse scenarios. Performance was assessed using commonly defined measures. Although no single method performed best across all scenarios, the results revealed clear differences between the various approaches, leading to notable practical conclusions for users and developers.
Journal of Computational Physics | 2006
Ivo F. Sbalzarini; Jens Honore Walther; Michael Bergdorf; Simone Elke Hieber; Evangelos M. Kotsalis; Petros Koumoutsakos
This paper presents a highly efficient parallel particle-mesh (PPM) library, based on a unifying particle formulation for the simulation of continuous systems. In this formulation, the grid-free character of particle methods is relaxed by the introduction of a mesh for the reinitialization of the particles, the computation of the field equations, and the discretization of differential operators. The present utilization of the mesh does not detract from the adaptivity, the efficient handling of complex geometries, the minimal dissipation, and the good stability properties of particle methods.The coexistence of meshes and particles, allows for the development of a consistent and adaptive numerical method, but it presents a set of challenging parallelization issues that have hindered in the past the broader use of particle methods. The present library solves the key parallelization issues involving particle-mesh interpolations and the balancing of processor particle loading, using a novel adaptive tree for mixed domain decompositions along with a coloring scheme for the particle-mesh interpolation.The high parallel efficiency of the library is demonstrated in a series of benchmark tests on distributed memory and on a shared-memory vector architecture. The modularity of the method is shown by a range of simulations, from compressible vortex rings using a novel formulation of smooth particle hydrodynamics, to simulations of diffusion in real biological cell organelles.The present library enables large scale simulations of diverse physical problems using adaptive particle methods and provides a computational tool that is a viable alternative to mesh-based methods.
Journal of Cell Biology | 2005
Cosima Luedeke; Stéphanie Buvelot Frei; Ivo F. Sbalzarini; Heinz Schwarz; Anne Spang; Yves Barral
Polarized cells frequently use diffusion barriers to separate plasma membrane domains. It is unknown whether diffusion barriers also compartmentalize intracellular organelles. We used photobleaching techniques to characterize protein diffusion in the yeast endoplasmic reticulum (ER). Although a soluble protein diffused rapidly throughout the ER lumen, diffusion of ER membrane proteins was restricted at the bud neck. Ultrastructural studies and fluorescence microscopy revealed the presence of a ring of smooth ER at the bud neck. This ER domain and the restriction of diffusion for ER membrane proteins through the bud neck depended on septin function. The membrane-associated protein Bud6 localized to the bud neck in a septin-dependent manner and was required to restrict the diffusion of ER membrane proteins. Our results indicate that Bud6 acts downstream of septins to assemble a fence in the ER membrane at the bud neck. Thus, in polarized yeast cells, diffusion barriers compartmentalize the ER and the plasma membrane along parallel lines.
Nano Letters | 2009
Harvey Zambrano; Jens Honore Walther; Petros Koumoutsakos; Ivo F. Sbalzarini
We study the thermophoretic motion of water nanodroplets confined inside carbon nanotubes using molecular dynamics simulations. We find that the nanodroplets move in the direction opposite the imposed thermal gradient with a terminal velocity that is linearly proportional to the gradient. The translational motion is associated with a solid body rotation of the water nanodroplet coinciding with the helical symmetry of the carbon nanotube. The thermal diffusion displays a weak dependence on the wetting of the water-carbon nanotube interface. We introduce the use of the moment scaling spectrum (MSS) in order to determine the characteristics of the motion of the nanoparticles inside the carbon nanotube. The MSS indicates that affinity of the nanodroplet with the walls of the carbon nanotubes is important for the isothermal diffusion and hence for the Soret coefficient of the system.
Journal of Chemical Physics | 2009
Rajesh Ramaswamy; Nélido González-Segredo; Ivo F. Sbalzarini
We introduce an alternative formulation of the exact stochastic simulation algorithm (SSA) for sampling trajectories of the chemical master equation for a well-stirred system of coupled chemical reactions. Our formulation is based on factored-out, partial reaction propensities. This novel exact SSA, called the partial-propensity direct method (PDM), is highly efficient and has a computational cost that scales at most linearly with the number of chemical species, irrespective of the degree of coupling of the reaction network. In addition, we propose a sorting variant, SPDM, which is especially efficient for multiscale reaction networks.
Journal of Microscopy | 2012
Mark E. Ambühl; C. Brepsant; Jean-Jacques Meister; Alexander B. Verkhovsky; Ivo F. Sbalzarini
Accurate extraction of cell outlines from microscopy images is essential for analysing the dynamics of migrating cells. Phase‐contrast microscopy is one of the most common and convenient imaging modalities for observing cell motility because it does not require exogenous labelling and uses only moderate light levels with generally negligible phototoxicity effects. Automatic extraction and tracking of high‐resolution cell outlines from phase‐contrast images, however, is difficult due to complex and non‐uniform edge intensity. We present a novel image‐processing method based on refined level‐set segmentation for accurate extraction of cell outlines from high‐resolution phase‐contrast images. The algorithm is validated on synthetic images of defined noise levels and applied to real image sequences of polarizing and persistently migrating keratocyte cells. We demonstrate that the algorithm is able to reliably reveal fine features in the cell edge dynamics.
International Journal of Computer Vision | 2013
Grégory Paul; Janick Cardinale; Ivo F. Sbalzarini
We introduce a new class of data-fitting energies that couple image segmentation with image restoration. These functionals model the image intensity using the statistical framework of generalized linear models. By duality, we establish an information-theoretic interpretation using Bregman divergences. We demonstrate how this formulation couples in a principled way image restoration tasks such as denoising, deblurring (deconvolution), and inpainting with segmentation. We present an alternating minimization algorithm to solve the resulting composite photometric/geometric inverse problem. We use Fisher scoring to solve the photometric problem and to provide asymptotic uncertainty estimates. We derive the shape gradient of our data-fitting energy and investigate convex relaxation for the geometric problem. We introduce a new alternating split-Bregman strategy to solve the resulting convex problem and present experiments and comparisons on both synthetic and real-world images.
congress on evolutionary computation | 2009
Christian L. M uller; Benedikt Baumgartner; Ivo F. Sbalzarini
We extend the Evolution Strategy with Covariance Matrix Adaptation (CMA-ES) by collaborative concepts from Particle Swarm Optimization (PSO). The proposed Particle Swarm CMA-ES (PS-CMA-ES) algorithm is a hybrid real-parameter algorithm that combines the robust local search performance of CMA-ES with the global exploration power of PSO using multiple CMA-ES instances to explore different parts of the search space in parallel. Swarm intelligence is introduced by considering individual CMA-ES instances as lumped particles that communicate with each other. This includes non-local information in CMA-ES, which improves the search direction and the sampling distribution. We evaluate the performance of PS-CMA-ES on the IEEE CEC 2005 benchmark test suite. The new PS-CMA-ES algorithm shows superior performance on noisy problems and multi-funnel problems with non-convex underlying topology.
PLOS Pathogens | 2011
Yohei Yamauchi; Heithem Boukari; Indranil Banerjee; Ivo F. Sbalzarini; Peter Horvath; Ari Helenius
Influenza A virus (IAV) enters host cells by endocytosis followed by acid-activated penetration from late endosomes (LEs). Using siRNA silencing, we found that histone deacetylase 8 (HDAC8), a cytoplasmic enzyme, efficiently promoted productive entry of IAV into tissue culture cells, whereas HDAC1 suppressed it. HDAC8 enhanced endocytosis, acidification, and penetration of the incoming virus. In contrast, HDAC1 inhibited acidification and penetration. The effects were connected with dramatic alterations in the organization of the microtubule system, and, as a consequence, a change in the behavior of LEs and lysosomes (LYs). Depletion of HDAC8 caused loss of centrosome-associated microtubules and loss of directed centripetal movement of LEs, dispersing LE/LYs to the cell periphery. For HDAC1, the picture was the opposite. To explain these changes, centrosome cohesion emerged as the critical factor. Depletion of HDAC8 caused centrosome splitting, which could also be induced by depleting a centriole-linker protein, rootletin. In both cases, IAV infection was inhibited. HDAC1 depletion reduced the splitting of centrosomes, and enhanced infection. The longer the distance between centrosomes, the lower the level of infection. HDAC8 depletion was also found to inhibit infection of Uukuniemi virus (a bunyavirus) suggesting common requirements among late penetrating enveloped viruses. The results established class I HDACs as powerful regulators of microtubule organization, centrosome function, endosome maturation, and infection by IAV and other late penetrating viruses.
Journal of Structural Biology | 2009
Jo A. Helmuth; Christoph J. Burckhardt; Urs F. Greber; Ivo F. Sbalzarini
Live imaging of subcellular structures is indispensible to advance our understanding of cellular processes. The blurred digital images acquired in light microscopy are, however, complex to analyze, and identification and reconstruction of subcellular structures from such images remains a major challenge. We present a novel, model-based image analysis algorithm to reconstruct outlines of subcellular structures using a sub-pixel representation. The algorithm explicitly accounts for the optical properties of the microscope. We validate the reconstruction performance on synthetic data and apply the new method to fluorescence microscopy images of endosomes identified by the GTPase EGFP-Rab5. The benefits of the new algorithm are outlined by comparison to standard techniques. We demonstrate that the new algorithm leads to better discrimination between different endosomal virus entry pathways and to more robust, accurate, and self-consistent quantification of endosome shape features. This allows establishing a set of features that quantify endosome morphology and robustly capture the dynamics of endosome fusion.