TY - JOUR
AB - The development of multicellular organisms is dependent on the tight coordination between tissue growth and morphogenesis. The stereotypical orientation of cell divisions has been proposed to be a fundamental mechanism by which proliferating and growing tissues take shape. However, the actual contribution of stereotypical division orientation (SDO) to tissue morphogenesis is unclear. In zebrafish, cell divisions with stereotypical orientation have been implicated in both body-axis elongation and neural rod formation [1, 2], although there is little direct evidence for a critical function of SDO in either of these processes. Here we show that SDO is required for formation of the neural rod midline during neurulation but dispensable for elongation of the body axis during gastrulation. Our data indicate that SDO during both gastrulation and neurulation is dependent on the noncanonical Wnt receptor Frizzled 7 (Fz7) and that interfering with cell division orientation leads to severe defects in neural rod midline formation but not body-axis elongation. These findings suggest a novel function for Fz7-controlled cell division orientation in neural rod midline formation during neurulation.
AU - Quesada-Hernández, Elena
AU - Caneparo, Luca
AU - Schneider, Sylvia
AU - Winkler, Sylke
AU - Liebling, Michael
AU - Fraser, Scott
AU - Heisenberg, Carl-Philipp J
ID - 3789
IS - 21
JF - Current Biology
TI - Stereotypical cell division orientation controls neural rod midline formation in zebrafish
VL - 20
ER -
TY - JOUR
AB - Cell shape and motility are primarily controlled by cellular mechanics. The attachment of the plasma membrane to the underlying actomyosin cortex has been proposed to be important for cellular processes involving membrane deformation. However, little is known about the actual function of membrane-to-cortex attachment (MCA) in cell protrusion formation and migration, in particular in the context of the developing embryo. Here, we use a multidisciplinary approach to study MCA in zebrafish mesoderm and endoderm (mesendoderm) germ layer progenitor cells, which migrate using a combination of different protrusion types, namely, lamellipodia, filopodia, and blebs, during zebrafish gastrulation. By interfering with the activity of molecules linking the cortex to the membrane and measuring resulting changes in MCA by atomic force microscopy, we show that reducing MCA in mesendoderm progenitors increases the proportion of cellular blebs and reduces the directionality of cell migration. We propose that MCA is a key parameter controlling the relative proportions of different cell protrusion types in mesendoderm progenitors, and thus is key in controlling directed migration during gastrulation.
AU - Diz Muñoz, Alba
AU - Krieg, Michael
AU - Bergert, Martin
AU - Ibarlucea Benitez, Itziar
AU - Müller, Daniel
AU - Paluch, Ewa
AU - Heisenberg, Carl-Philipp J
ID - 3790
IS - 11
JF - PLoS Biology
TI - Control of directed cell migration in vivo by membrane-to-cortex attachment
VL - 8
ER -
TY - JOUR
AB - The yolk syncytial layer (YSL) plays crucial roles in early zebrafish development. The YSL is a transient extra-embryonic syncytial tissue that forms during early cleavage stages and persists until larval stages. During gastrulation, the YSL undergoes highly dynamic movements, which are tightly coordinated with the movements of the overlying germ layer progenitor cells, and has critical functions in cell fate specification and morphogenesis of the early germ layers. Movement coordination between the YSL and blastoderm cells is dependent on contact between these tissues, and is probably required for the patterning and morphogenetic function of the YSL. In this review, we will discuss recent advances in elucidating the molecular and cellular mechanisms underlying the YSL morphogenesis and movement coordination between the YSL and blastoderm during early development.
AU - Carvalho, Lara
AU - Heisenberg, Carl-Philipp J
ID - 3792
IS - 10
JF - Trends in Cell Biology
TI - The yolk syncytial layer in early, zebrafish development
VL - 20
ER -
TY - CONF
AB - Recent progress in per-pixel object class labeling of natural images can be attributed to the use of multiple types of image features and sound statistical learning approaches. Within the latter, Conditional Random Fields (CRF) are prominently used for their ability to represent interactions between random variables. Despite their popularity in computer vision, parameter learning for CRFs has remained difficult, popular approaches being cross-validation and piecewise training.
In this work, we propose a simple yet expressive tree-structured CRF based on a recent hierarchical image segmentation method. Our model combines and weights multiple image features within a hierarchical representation and allows simple and efficient globally-optimal learning of ≈ 105 parameters. The tractability of our model allows us to pose and answer some of the open questions regarding parameter learning applying to CRF-based approaches. The key findings for learning CRF models are, from the obvious to the surprising, i) multiple image features always help, ii) the limiting dimension with respect to current models is the amount of training data, iii) piecewise training is competitive, iv) current methods for max-margin training fail for models with many parameters.
AU - Nowozin, Sebastian
AU - Gehler, Peter
AU - Lampert, Christoph
ID - 3793
TI - On parameter learning in CRF-based approaches to object class image segmentation
VL - 6316
ER -
TY - CONF
AB - We study the problem of multimodal dimensionality reduction assuming that data samples can be missing at training time, and not all data modalities may be present at application time. Maximum covariance analysis, as a generalization of PCA, has many desirable properties, but its application to practical problems is limited by its need for perfectly paired data. We overcome this limitation by a latent variable approach that allows working with weakly paired data and is still able to efficiently process large datasets using standard numerical routines. The resulting weakly paired maximum covariance analysis often finds better representations than alternative methods, as we show in two exemplary tasks: texture discrimination and transfer learning.
AU - Lampert, Christoph
AU - Krömer, Oliver
ID - 3794
TI - Weakly-paired maximum covariance analysis for multimodal dimensionality reduction and transfer learning
VL - 6312
ER -
TY - CHAP
AB - The (apparent) contour of a smooth mapping from a 2-manifold to the plane, f: M → R2 , is the set of critical values, that is, the image of the points at which the gradients of the two component functions are linearly dependent. Assuming M is compact and orientable and measuring difference with the erosion distance, we prove that the contour is stable.
AU - Edelsbrunner, Herbert
AU - Morozov, Dmitriy
AU - Patel, Amit
ID - 3795
T2 - Topological Data Analysis and Visualization: Theory, Algorithms and Applications
TI - The stability of the apparent contour of an orientable 2-manifold
ER -
TY - JOUR
AB - A recent paper by von Engelhardt et al. identifies a novel auxiliary subunit of native AMPARs, termedCKAMP44. Unlike other auxiliary subunits, CKAMP44 accelerates desensitization and prolongs recovery from desensitization. CKAMP44 is highly expressed in hippocampal dentate gyrus granule cells and decreases the paired-pulse ratio at perforant path input synapses. Thus, both principal and auxiliary AMPAR subunits control the time course of signaling at glutamatergic synapses.
AU - Guzmán, José
AU - Jonas, Peter M
ID - 3832
IS - 1
JF - Neuron
TI - Beyond TARPs: The growing list of auxiliary AMPAR subunits
VL - 66
ER -
TY - JOUR
AU - Jonas, Peter M
AU - Hefft, Stefan
ID - 3833
IS - 7
JF - The European Journal of Neuroscience
TI - GABA release at terminals of CCK-interneurons: synchrony, asynchrony and modulation by cannabinoid receptors (commentary on Ali & Todorova)
VL - 31
ER -
TY - JOUR
AB - Background
The chemical master equation (CME) is a system of ordinary differential equations that describes the evolution of a network of chemical reactions as a stochastic process. Its solution yields the probability density vector of the system at each point in time. Solving the CME numerically is in many cases computationally expensive or even infeasible as the number of reachable states can be very large or infinite. We introduce the sliding window method, which computes an approximate solution of the CME by performing a sequence of local analysis steps. In each step, only a manageable subset of states is considered, representing a "window" into the state space. In subsequent steps, the window follows the direction in which the probability mass moves, until the time period of interest has elapsed. We construct the window based on a deterministic approximation of the future behavior of the system by estimating upper and lower bounds on the populations of the chemical species.
Results
In order to show the effectiveness of our approach, we apply it to several examples previously described in the literature. The experimental results show that the proposed method speeds up the analysis considerably, compared to a global analysis, while still providing high accuracy.
Conclusions
The sliding window method is a novel approach to address the performance problems of numerical algorithms for the solution of the chemical master equation. The method efficiently approximates the probability distributions at the time points of interest for a variety of chemically reacting systems, including systems for which no upper bound on the population sizes of the chemical species is known a priori.
AU - Wolf, Verena
AU - Goel, Rushil
AU - Mateescu, Maria
AU - Henzinger, Thomas A
ID - 3834
IS - 42
JF - BMC Systems Biology
TI - Solving the chemical master equation using sliding windows
VL - 4
ER -
TY - CONF
AB - We present a numerical approximation technique for the analysis of continuous-time Markov chains that describe net- works of biochemical reactions and play an important role in the stochastic modeling of biological systems. Our approach is based on the construction of a stochastic hybrid model in which certain discrete random variables of the original Markov chain are approximated by continuous deterministic variables. We compute the solution of the stochastic hybrid model using a numerical algorithm that discretizes time and in each step performs a mutual update of the transient prob- ability distribution of the discrete stochastic variables and the values of the continuous deterministic variables. We im- plemented the algorithm and we demonstrate its usefulness and efficiency on several case studies from systems biology.
AU - Henzinger, Thomas A
AU - Mateescu, Maria
AU - Mikeev, Linar
AU - Wolf, Verena
ID - 3838
TI - Hybrid numerical solution of the chemical master equation
ER -
TY - CONF
AB - We present a loop property generation method for loops iterating over multi-dimensional arrays. When used on matrices, our method is able to infer their shapes (also called types), such as upper-triangular, diagonal, etc. To gen- erate loop properties, we first transform a nested loop iterating over a multi- dimensional array into an equivalent collection of unnested loops. Then, we in- fer quantified loop invariants for each unnested loop using a generalization of a recurrence-based invariant generation technique. These loop invariants give us conditions on matrices from which we can derive matrix types automatically us- ing theorem provers. Invariant generation is implemented in the software package Aligator and types are derived by theorem provers and SMT solvers, including Vampire and Z3. When run on the Java matrix package JAMA, our tool was able to infer automatically all matrix types describing the matrix shapes guaranteed by JAMA’s API.
AU - Henzinger, Thomas A
AU - Hottelier, Thibaud
AU - Kovács, Laura
AU - Voronkov, Andrei
ID - 3839
TI - Invariant and type inference for matrices
VL - 5944
ER -
TY - CONF
AB - Classical formalizations of systems and properties are boolean: given a system and a property, the property is either true or false of the system. Correspondingly, classical methods for system analysis determine the truth value of a property, preferably giving a proof if the property is true, and a counterexample if the property is false; classical methods for system synthesis construct a system for which a property is true; classical methods for system transformation, composition, and abstraction aim to preserve the truth of properties. The boolean view is prevalent even if the system, the property, or both refer to numerical quantities, such as the times or probabilities of events. For example, a timed automaton either satisfies or violates a formula of a real-time logic; a stochastic process either satisfies or violates a formula of a probabilistic logic. The classical black-and-white view partitions the world into "correct" and "incorrect" systems, offering few nuances. In reality, of several systems that satisfy a property in the boolean sense, often some are more desirable than others, and of the many systems that violate a property, usually some are less objectionable than others. For instance, among the systems that satisfy the response property that every request be granted, we may prefer systems that grant requests quickly (the quicker, the better), or we may prefer systems that issue few unnecessary grants (the fewer, the better); and among the systems that violate the response property, we may prefer systems that serve many initial requests (the more, the better), or we may prefer systems that serve many requests in the long run (the greater the fraction of served to unserved requests, the better). Formally, while a boolean notion of correctness is given by a preorder on systems and properties, a quantitative notion of correctness is defined by a directed metric on systems and properties, where the distance between a system and a property provides a measure of "fit" or "desirability." There are many ways how such distances can be defined. In a linear-time framework, one assigns numerical values to individual behaviors before assigning values to systems and properties, which are sets of behaviors. For example, the value of a single behavior may be a discounted value, which is largely determined by a prefix of the behavior, e.g., by the number of requests that are granted before the first request that is not granted; or a limit value, which is independent of any finite prefix. A limit value may be an average, such as the average response time over an infinite sequence of requests and grants, or a supremum, such as the worst-case response time. Similarly, the value of a set of behaviors may be an extremum or an average across the values of all behaviors in the set: in this way one can measure the worst of all possible average-case response times, or the average of all possible worst-case response times, etc. Accordingly, the distance between two sets of behaviors may be defined as the worst or average difference between the values of corresponding behaviors. In summary, we propagate replacing boolean specifications for the correctness of systems with quantitative measures for the desirability of systems. In quantitative analysis, the aim is to compute the distance between a system and a property (or between two systems, or two properties); in quantitative synthesis, the objective is to construct a system that has minimal distance from a given property. Multiple quantitative measures can be prioritized (e.g., combined lexicographically into a single measure) or studied along the Pareto curve. Quantitative transformations, compositions, and abstractions of systems are useful if they allow us to bound the induced change in distance from a property. We present some initial results in some of these directions. We also give some potential applications, which not only generalize tradiditional correctness concerns in the functional, timed, and probabilistic domains, but also capture such system measures as resource use, performance, cost, reliability, and robustness.
AU - Henzinger, Thomas A
ID - 3840
IS - 1
TI - From boolean to quantitative notions of correctness
VL - 45
ER -
TY - JOUR
AB - Within systems biology there is an increasing interest in the stochastic behavior of biochemical reaction networks. An appropriate stochastic description is provided by the chemical master equation, which represents a continuous-time Markov chain (CTMC). The uniformization technique is an efficient method to compute probability distributions of a CTMC if the number of states is manageable. However, the size of a CTMC that represents a biochemical reaction network is usually far beyond what is feasible. In this paper we present an on-the-fly variant of uniformization, where we improve the original algorithm at the cost of a small approximation error. By means of several examples, we show that our approach is particularly well-suited for biochemical reaction networks.
AU - Didier, Frédéric
AU - Henzinger, Thomas A
AU - Mateescu, Maria
AU - Wolf, Verena
ID - 3842
IS - 6
JF - IET Systems Biology
TI - Fast adaptive uniformization of the chemical master equation
VL - 4
ER -
TY - CONF
AB - This paper presents Aligators, a tool for the generation of universally quantified array invariants. Aligators leverages recurrence solving and algebraic techniques to carry out inductive reasoning over array content. The Aligators’ loop extraction module allows treatment of multi-path loops by exploiting their commutativity and serializability properties. Our experience in applying Aligators on a collection of loops from open source software projects indicates the applicability of recurrence and algebraic solving techniques for reasoning about arrays.
AU - Henzinger, Thomas A
AU - Hottelier, Thibaud
AU - Kovács, Laura
AU - Rybalchenko, Andrey
ID - 3845
TI - Aligators for arrays
VL - 6397
ER -
TY - CONF
AB - The importance of stochasticity within biological systems has been shown repeatedly during the last years and has raised the need for efficient stochastic tools. We present SABRE, a tool for stochastic analysis of biochemical reaction networks. SABRE implements fast adaptive uniformization (FAU), a direct numerical approximation algorithm for computing transient solutions of biochemical reaction networks. Biochemical reactions networks represent biological systems studied at a molecular level and these reactions can be modeled as transitions of a Markov chain. SABRE accepts as input the formalism of guarded commands, which it interprets either as continuous-time or as discrete-time Markov chains. Besides operating in a stochastic mode, SABRE may also perform a deterministic analysis by directly computing a mean-field approximation of the system under study. We illustrate the different functionalities of SABRE by means of biological case studies.
AU - Didier, Frédéric
AU - Henzinger, Thomas A
AU - Mateescu, Maria
AU - Wolf, Verena
ID - 3847
TI - SABRE: A tool for the stochastic analysis of biochemical reaction networks
ER -
TY - CONF
AB - We define the robustness of a level set homology class of a function f:XR as the magnitude of a perturbation necessary to kill the class. Casting this notion into a group theoretic framework, we compute the robustness for each class, using a connection to extended persistent homology. The special case X=R3 has ramifications in medical imaging and scientific visualization.
AU - Bendich, Paul
AU - Edelsbrunner, Herbert
AU - Morozov, Dmitriy
AU - Patel, Amit
ID - 3848
TI - The robustness of level sets
VL - 6346
ER -
TY - CONF
AB - Using ideas from persistent homology, the robustness of a level set of a real-valued function is defined in terms of the magnitude of the perturbation necessary to kill the classes. Prior work has shown that the homology and robustness information can be read off the extended persistence diagram of the function. This paper extends these results to a non-uniform error model in which perturbations vary in their magnitude across the domain.
AU - Bendich, Paul
AU - Edelsbrunner, Herbert
AU - Kerber, Michael
AU - Patel, Amit
ID - 3849
TI - Persistent homology under non-uniform error
VL - 6281
ER -
TY - CONF
AB - Given a polygonal shape Q with n vertices, can it be expressed, up to a tolerance ε in Hausdorff distance, as the Minkowski sum of another polygonal shape with a disk of fixed radius? If it does, we also seek a preferably simple solution shape P;P’s offset constitutes an accurate, vertex-reduced, and smoothened approximation of Q. We give a decision algorithm for fixed radius in O(nlogn) time that handles any polygonal shape. For convex shapes, the complexity drops to O(n), which is also the time required to compute a solution shape P with at most one more vertex than a vertex-minimal one.
AU - Berberich, Eric
AU - Halperin, Dan
AU - Kerber, Michael
AU - Pogalnikova, Roza
ID - 3850
TI - Polygonal reconstruction from approximate offsets
ER -
TY - CONF
AB - Energy parity games are infinite two-player turn-based games played on weighted graphs. The objective of the game combines a (qualitative) parity condition with the (quantitative) requirement that the sum of the weights (i.e., the level of energy in the game) must remain positive. Beside their own interest in the design and synthesis of resource-constrained omega-regular specifications, energy parity games provide one of the simplest model of games with combined qualitative and quantitative objective. Our main results are as follows: (a) exponential memory is sufficient and may be necessary for winning strategies in energy parity games; (b) the problem of deciding the winner in energy parity games can be solved in NP ∩ coNP; and (c) we give an algorithm to solve energy parity by reduction to energy games. We also show that the problem of deciding the winner in energy parity games is polynomially equivalent to the problem of deciding the winner in mean-payoff parity games, which can thus be solved in NP ∩ coNP. As a consequence we also obtain a conceptually simple algorithm to solve mean-payoff parity games.
AU - Chatterjee, Krishnendu
AU - Doyen, Laurent
ID - 3851
TI - Energy parity games
VL - 6199
ER -
TY - CONF
AB - We introduce two-level discounted games played by two players on a perfect-information stochastic game graph. The upper level game is a discounted game and the lower level game is an undiscounted reachability game. Two-level games model hierarchical and sequential decision making under uncertainty across different time scales. We show the existence of pure memoryless optimal strategies for both players and an ordered field property for such games. We show that if there is only one player (Markov decision processes), then the values can be computed in polynomial time. It follows that whether the value of a player is equal to a given rational constant in two-level discounted games can be decided in NP intersected coNP. We also give an alternate strategy improvement algorithm to compute the value.
AU - Chatterjee, Krishnendu
AU - Majumdar, Ritankar
ID - 3852
TI - Discounting in games across time scales
VL - 25
ER -