TY - CHAP
AB - In this paper we present an efficient framework for computation of persis- tent homology of cubical data in arbitrary dimensions. An existing algorithm using simplicial complexes is adapted to the setting of cubical complexes. The proposed approach enables efficient application of persistent homology in domains where the data is naturally given in a cubical form. By avoiding triangulation of the data, we significantly reduce the size of the complex. We also present a data-structure de- signed to compactly store and quickly manipulate cubical complexes. By means of numerical experiments, we show high speed and memory efficiency of our ap- proach. We compare our framework to other available implementations, showing its superiority. Finally, we report performance on selected 3D and 4D data-sets.
AU - Wagner, Hubert
AU - Chen, Chao
AU - Vuçini, Erald
ED - Peikert, Ronald
ED - Hauser, Helwig
ED - Carr, Hamish
ED - Fuchs, Raphael
ID - 3271
T2 - Topological Methods in Data Analysis and Visualization II
TI - Efficient computation of persistent homology for cubical data
ER -
TY - THES
AU - Maître, Jean-Léon
ID - 3273
TI - Mechanics of adhesion and de‐adhesion in zebrafish germ layer progenitors
ER -
TY - THES
AB - Chemokines organize immune cell trafficking by inducing either directed (tactic) or random (kinetic) migration and by activating integrins in order to support surface adhesion (haptic). Beyond that the same chemokines can establish clearly defined functional areas in secondary lymphoid organs. Until now it is unclear how chemokines can fulfill such diverse functions. One decisive prerequisite to explain these capacities is to know how chemokines are presented in tissue. In theory chemokines could occur either soluble or immobilized, and could be distributed either homogenously or as a concentration gradient. To dissect if and how the presenting mode of chemokines influences immune cells, I tested the response of dendritic cells (DCs) to differentially displayed chemokines. DCs are antigen presenting cells that reside in the periphery and migrate into draining lymph nodes (LNs) once exposed to inflammatory stimuli to activate naïve T cells. DCs are guided to and within the LN by the chemokine receptor CCR7, which has two ligands, the chemokines CCL19 and CCL21. Both CCR7 ligands are expressed by fibroblastic reticular cells in the LN, but differ in their ability to bind to heparan sulfate residues. CCL21 has a highly charged C-terminal extension, which mediates binding to anionic surfaces, whereas CCL19 is lacking such residues and likely distributes as a soluble molecule. This study shows that surface-bound CCL21 causes random, haptokinetic DC motility, which is confined to the chemokine coated area by insideout activation of β2 integrins that mediate cell binding to the surface. CCL19 on the other hand forms concentration gradients which trigger directional, chemotactic movement, but no surface adhesion. In addition DCs can actively manipulate this system by recruiting and activating serine proteases on their surfaces, which create - by proteolytically removing the adhesive C-terminus - a solubilized variant of CCL21 that functionally resembles CCL19. By generating a CCL21 concentration gradient DCs establish a positive feedback loop to recruit further DCs from the periphery to the CCL21 coated region. In addition DCs can sense chemotactic gradients as well as immobilized haptokinetic fields at the same time and integrate these signals. The result is chemotactically biased haptokinesis - directional migration confined to a chemokine coated track or area - which could explain the dynamic but spatially tightly controlled swarming leukocyte locomotion patterns that have been observed in lymphatic organs by intravital microscopists. The finding that DCs can approach soluble cues in a non-adhesive manner while they attach to surfaces coated with immobilized cues raises the question how these cells transmit intracellular forces to the environment, especially in the non-adherent migration mode. In order to migrate, cells have to generate and transmit force to the extracellular substrate. Force transmission is the prerequisite to procure an expansion of the leading edge and a forward motion of the whole cell body. In the current conceptions actin polymerization at the leading edge is coupled to extracellular ligands via the integrin family of transmembrane receptors, which allows the transmission of intracellular force. Against the paradigm of force transmission during migration, leukocytes, like DCs, are able to migrate in threedimensional environments without using integrin transmembrane receptors (Lämmermann et al., 2008). This reflects the biological function of leukocytes, as they can invade almost all tissues, whereby their migration has to be independent from the extracellular environment. How the cells can achieve this is unclear. For this study I examined DC migration in a defined threedimensional environment and highlighted actin-dynamics with the probe Lifeact-GFP. The result was that chemotactic DCs can switch between integrin-dependent and integrin- independent locomotion and can thereby adapt to the adhesive properties of their environment. If the cells are able to couple their actin cytoskeleton to the substrate, actin polymerization is entirely converted into protrusion. Without coupling the actin cortex undergoes slippage and retrograde actin flow can be observed. But retrograde actin flow can be completely compensated by higher actin polymerization rate keeping the migration velocity and the shape of the cells unaltered. Mesenchymal cells like fibroblast cannot balance the loss of adhesive interaction, cannot protrude into open space and, therefore, strictly depend on integrinmediated force coupling. This leukocyte specific phenomenon of “adaptive force transmission” endows these cells with the unique ability to transit and invade almost every type of tissue.
AU - Schumann, Kathrin
ID - 3275
TI - The role of chemotactic gradients in dendritic cell migration
ER -
TY - JOUR
AB - Diffusing membrane constituents are constantly exposed to a variety of forces that influence their stochastic path. Single molecule experiments allow for resolving trajectories at extremely high spatial and temporal accuracy, thereby offering insights into en route interactions of the tracer. In this review we discuss approaches to derive information about the underlying processes, based on single molecule tracking experiments. In particular, we focus on a new versatile way to analyze single molecule diffusion in the absence of a full analytical treatment. The method is based on comprehensive comparison of an experimental data set against the hypothetical outcome of multiple experiments performed on the computer. Since Monte Carlo simulations can be easily and rapidly performed even on state-of-the-art PCs, our method provides a simple way for testing various - even complicated - diffusion models. We describe the new method in detail, and show the applicability on two specific examples: firstly, kinetic rate constants can be derived for the transient interaction of mobile membrane proteins; secondly, residence time and corral size can be extracted for confined diffusion.
AU - Ruprecht, Verena
AU - Axmann, Markus
AU - Wieser, Stefan
AU - Schuetz, Gerhard
ID - 3287
IS - 8
JF - Current Protein & Peptide Science
TI - What can we learn from single molecule trajectories?
VL - 12
ER -
TY - JOUR
AB - The zonula adherens (ZA) of epithelial cells is a site of cell-cell adhesion where cellular forces are exerted and resisted. Increasing evidence indicates that E-cadherin adhesion molecules at the ZA serve to sense force applied on the junctions and coordinate cytoskeletal responses to those forces. Efforts to understand the role that cadherins play in mechanotransduction have been limited by the lack of assays to measure the impact of forces on the ZA. In this study we used 4D imaging of GFP-tagged E-cadherin to analyse the movement of the ZA. Junctions in confluent epithelial monolayers displayed prominent movements oriented orthogonal (perpendicular) to the ZA itself. Two components were identified in these movements: a relatively slow unidirectional (translational) component that could be readily fitted by least-squares regression analysis, upon which were superimposed more rapid oscillatory movements. Myosin IIB was a dominant factor responsible for driving the unilateral translational movements. In contrast, frequency spectrum analysis revealed that depletion of Myosin IIA increased the power of the oscillatory movements. This implies that Myosin IIA may serve to dampen oscillatory movements of the ZA. This extends our recent analysis of Myosin II at the ZA to demonstrate that Myosin IIA and Myosin IIB make distinct contributions to junctional movement at the ZA.
AU - Smutny, Michael
AU - Wu, Selwin
AU - Gomez, Guillermo
AU - Mangold, Sabine
AU - Yap, Alpha
AU - Hamilton, Nicholas
ID - 3288
IS - 7
JF - PLoS One
TI - Multicomponent analysis of junctional movements regulated by Myosin II isoforms at the epithelial zonula adherens
VL - 6
ER -
TY - JOUR
AB - Analysis of genomic data requires an efficient way to calculate likelihoods across very large numbers of loci. We describe a general method for finding the distribution of genealogies: we allow migration between demes, splitting of demes [as in the isolation-with-migration (IM) model], and recombination between linked loci. These processes are described by a set of linear recursions for the generating function of branch lengths. Under the infinite-sites model, the probability of any configuration of mutations can be found by differentiating this generating function. Such calculations are feasible for small numbers of sampled genomes: as an example, we show how the generating function can be derived explicitly for three genes under the two-deme IM model. This derivation is done automatically, using Mathematica. Given data from a large number of unlinked and nonrecombining blocks of sequence, these results can be used to find maximum-likelihood estimates of model parameters by tabulating the probabilities of all relevant mutational configurations and then multiplying across loci. The feasibility of the method is demonstrated by applying it to simulated data and to a data set previously analyzed by Wang and Hey (2010) consisting of 26,141 loci sampled from Drosophila simulans and D. melanogaster. Our results suggest that such likelihood calculations are scalable to genomic data as long as the numbers of sampled individuals and mutations per sequence block are small.
AU - Lohse, Konrad
AU - Harrison, Richard
AU - Barton, Nicholas H
ID - 3290
IS - 3
JF - Genetics
TI - A general method for calculating likelihoods under the coalescent process
VL - 189
ER -
TY - CONF
AB - Animating detailed liquid surfaces has always been a challenge for computer graphics researchers and visual effects artists. Over the past few years, researchers in this field have focused on mesh-based surface tracking to synthesize extremely detailed liquid surfaces as efficiently as possible. This course provides a solid understanding of the steps required to create a fluid simulator with a mesh-based liquid surface.
The course begins with an overview of several existing liquid-surface-tracking techniques and the pros and cons of each method. Then it explains how to embed a triangle mesh into a finite-difference-based fluid simulator and describes several methods for allowing the liquid surface to merge together or break apart. The final section showcases the benefits and further applications of a mesh-based liquid surface, highlighting state-of-the-art methods for tracking colors and textures, maintaining liquid volume, preserving small surface features, and simulating realistic surface-tension waves.
AU - Wojtan, Christopher J
AU - Müller Fischer, Matthias
AU - Brochu, Tyson
ID - 3297
TI - Liquid simulation with mesh-based surface tracking
ER -
TY - CONF
AB - We present a new algorithm for enforcing incompressibility for Smoothed Particle Hydrodynamics (SPH) by preserving uniform density across the domain. We propose a hybrid method that uses a Poisson solve on a coarse grid to enforce a divergence free velocity ﬁeld, followed by a local density correction of the particles. This avoids typical grid artifacts and maintains the Lagrangian nature of SPH by directly transferring pressures onto particles. Our method can be easily integrated with existing SPH techniques such as the incompressible PCISPH method as well as weakly compressible SPH by adding an additional force term. We show that this hybrid method accelerates convergence towards uniform density and permits a signiﬁcantly larger time step compared to earlier approaches while producing similar results. We demonstrate our approach in a variety of scenarios with signiﬁcant pressure gradients such as splashing liquids.
AU - Raveendran, Karthik
AU - Wojtan, Christopher J
AU - Turk, Greg
ED - Spencer, Stephen
ID - 3298
TI - Hybrid smoothed particle hydrodynamics
ER -
TY - CONF
AB - We introduce propagation models, a formalism designed to support general and efficient data structures for the transient analysis of biochemical reaction networks. We give two use cases for propagation abstract data types: the uniformization method and numerical integration. We also sketch an implementation of a propagation abstract data type, which uses abstraction to approximate states.
AU - Henzinger, Thomas A
AU - Mateescu, Maria
ID - 3299
TI - Propagation models for computing biochemical reaction networks
ER -
TY - CONF
AB - The chemical master equation is a differential equation describing the time evolution of the probability distribution over the possible “states” of a biochemical system. The solution of this equation is of interest within the systems biology field ever since the importance of the molec- ular noise has been acknowledged. Unfortunately, most of the systems do not have analytical solutions, and numerical solutions suffer from the course of dimensionality and therefore need to be approximated. Here, we introduce the concept of tail approximation, which retrieves an approximation of the probabilities in the tail of a distribution from the total probability of the tail and its conditional expectation. This approximation method can then be used to numerically compute the solution of the chemical master equation on a subset of the state space, thus fighting the explosion of the state space, for which this problem is renowned.
AU - Henzinger, Thomas A
AU - Mateescu, Maria
ID - 3301
TI - Tail approximation for the chemical master equation
ER -