TY - JOUR
AB - Nestin-cre transgenic mice have been widely used to direct recombination to neural stem cells (NSCs) and intermediate neural progenitor cells (NPCs). Here we report that a readily utilized, and the only commercially available, Nestin-cre line is insufficient for directing recombination in early embryonic NSCs and NPCs. Analysis of recombination efficiency in multiple cre-dependent reporters and a genetic mosaic line revealed consistent temporal and spatial patterns of recombination in NSCs and NPCs. For comparison we utilized a knock-in Emx1cre line and found robust recombination in NSCs and NPCs in ventricular and subventricular zones of the cerebral cortices as early as embryonic day 12.5. In addition we found that the rate of Nestin-cre driven recombination only reaches sufficiently high levels in NSCs and NPCs during late embryonic and early postnatal periods. These findings are important when commercially available cre lines are considered for directing recombination to embryonic NSCs and NPCs.
AU - Liang, Huixuan
AU - Hippenmeyer, Simon
AU - Ghashghaei, H.
ID - 2263
IS - 12
JF - Biology open
TI - A Nestin-cre transgenic mouse is insufficient for recombination in early embryonic neural progenitors
VL - 1
ER -
TY - JOUR
AB - We introduce propagation models (PMs), a formalism able to express several kinds of equations that describe the behavior of biochemical reaction networks. Furthermore, we introduce the propagation abstract data type (PADT), which separates concerns regarding different numerical algorithms for the transient analysis of biochemical reaction networks from concerns regarding their implementation, thus allowing for portable and efficient solutions. The state of a propagation abstract data type is given by a vector that assigns mass values to a set of nodes, and its (next) operator propagates mass values through this set of nodes. We propose an approximate implementation of the (next) operator, based on threshold abstraction, which propagates only "significant" mass values and thus achieves a compromise between efficiency and accuracy. Finally, we give three use cases for propagation models: the chemical master equation (CME), the reaction rate equation (RRE), and a hybrid method that combines these two equations. These three applications use propagation models in order to propagate probabilities and/or expected values and variances of the model's variables.
AU - Henzinger, Thomas A
AU - Mateescu, Maria
ID - 2302
IS - 2
JF - IEEE ACM Transactions on Computational Biology and Bioinformatics
TI - The propagation approach for computing biochemical reaction networks
VL - 10
ER -
TY - JOUR
AB - The kingdom of fungi provides model organisms for biotechnology, cell biology, genetics, and life sciences in general. Only when their phylogenetic relationships are stably resolved, can individual results from fungal research be integrated into a holistic picture of biology. However, and despite recent progress, many deep relationships within the fungi remain unclear. Here, we present the first phylogenomic study of an entire eukaryotic kingdom that uses a consistency criterion to strengthen phylogenetic conclusions. We reason that branches (splits) recovered with independent data and different tree reconstruction methods are likely to reflect true evolutionary relationships. Two complementary phylogenomic data sets based on 99 fungal genomes and 109 fungal expressed sequence tag (EST) sets analyzed with four different tree reconstruction methods shed light from different angles on the fungal tree of life. Eleven additional data sets address specifically the phylogenetic position of Blastocladiomycota, Ustilaginomycotina, and Dothideomycetes, respectively. The combined evidence from the resulting trees supports the deep-level stability of the fungal groups toward a comprehensive natural system of the fungi. In addition, our analysis reveals methodologically interesting aspects. Enrichment for EST encoded data-a common practice in phylogenomic analyses-introduces a strong bias toward slowly evolving and functionally correlated genes. Consequently, the generalization of phylogenomic data sets as collections of randomly selected genes cannot be taken for granted. A thorough characterization of the data to assess possible influences on the tree reconstruction should therefore become a standard in phylogenomic analyses.
AU - Ebersberger, Ingo
AU - De Matos Simoes, Ricardo
AU - Kupczok, Anne
AU - Gube, Matthias
AU - Kothe, Erika
AU - Voigt, Kerstin
AU - Von Haeseler, Arndt
ID - 2411
IS - 5
JF - Molecular Biology and Evolution
TI - A consistent phylogenetic backbone for the fungi
VL - 29
ER -
TY - JOUR
AB - We show that bosons interacting via pair potentials with negative scattering length form bound states for a suitable number of particles. In other words, the absence of many-particle bound states of any kind implies the non-negativity of the scattering length of the interaction potential.
AU - Seiringer, Robert
ID - 2318
IS - 3
JF - Journal of Spectral Theory
TI - Absence of bound states implies non-negativity of the scattering length
VL - 2
ER -
TY - CONF
AB - We consider Markov decision processes (MDPs) with specifications given as Büchi (liveness) objectives. We consider the problem of computing the set of almost-sure winning vertices from where the objective can be ensured with probability 1. We study for the first time the average case complexity of the classical algorithm for computing the set of almost-sure winning vertices for MDPs with Büchi objectives. Our contributions are as follows: First, we show that for MDPs with constant out-degree the expected number of iterations is at most logarithmic and the average case running time is linear (as compared to the worst case linear number of iterations and quadratic time complexity). Second, for the average case analysis over all MDPs we show that the expected number of iterations is constant and the average case running time is linear (again as compared to the worst case linear number of iterations and quadratic time complexity). Finally we also show that given that all MDPs are equally likely, the probability that the classical algorithm requires more than constant number of iterations is exponentially small.
AU - Chatterjee, Krishnendu
AU - Joglekar, Manas
AU - Shah, Nisarg
ID - 2715
TI - Average case analysis of the classical algorithm for Markov decision processes with Büchi objectives
VL - 18
ER -
TY - CONF
AB - We study the problem of maximum marginal prediction (MMP) in probabilistic graphical models, a task that occurs, for example, as the Bayes optimal decision rule under a Hamming loss. MMP is typically performed as a two-stage procedure: one estimates each variable's marginal probability and then forms a prediction from the states of maximal probability. In this work we propose a simple yet effective technique for accelerating MMP when inference is sampling-based: instead of the above two-stage procedure we directly estimate the posterior probability of each decision variable. This allows us to identify the point of time when we are sufficiently certain about any individual decision. Whenever this is the case, we dynamically prune the variables we are confident about from the underlying factor graph. Consequently, at any time only samples of variables whose decision is still uncertain need to be created. Experiments in two prototypical scenarios, multi-label classification and image inpainting, show that adaptive sampling can drastically accelerate MMP without sacrificing prediction accuracy.
AU - Lampert, Christoph
ID - 2825
TI - Dynamic pruning of factor graphs for maximum marginal prediction
VL - 1
ER -
TY - JOUR
AB - We study evolutionary game theory in a setting where individuals learn from each other. We extend the traditional approach by assuming that a population contains individuals with different learning abilities. In particular, we explore the situation where individuals have different search spaces, when attempting to learn the strategies of others. The search space of an individual specifies the set of strategies learnable by that individual. The search space is genetically given and does not change under social evolutionary dynamics. We introduce a general framework and study a specific example in the context of direct reciprocity. For this example, we obtain the counter intuitive result that cooperation can only evolve for intermediate benefit-to-cost ratios, while small and large benefit-to-cost ratios favor defection. Our paper is a step toward making a connection between computational learning theory and evolutionary game dynamics.
AU - Chatterjee, Krishnendu
AU - Zufferey, Damien
AU - Nowak, Martin
ID - 2848
JF - Journal of Theoretical Biology
TI - Evolutionary game dynamics in populations with different learners
VL - 301
ER -
TY - JOUR
AU - Edelsbrunner, Herbert
AU - Strelkova, Nataliya
ID - 2849
IS - 6
JF - Russian Mathematical Surveys
TI - On the configuration space of Steiner minimal trees
VL - 67
ER -
TY - CONF
AB - Formal verification aims to improve the quality of hardware and software by detecting errors before they do harm. At the basis of formal verification lies the logical notion of correctness, which purports to capture whether or not a circuit or program behaves as desired. We suggest that the boolean partition into correct and incorrect systems falls short of the practical need to assess the behavior of hardware and software in a more nuanced fashion against multiple criteria.
AU - Henzinger, Thomas A
ID - 2888
T2 - Conference proceedings MODELS 2012
TI - Quantitative reactive models
VL - 7590
ER -
TY - CONF
AB - Systems are often specified using multiple requirements on their behavior. In practice, these requirements can be contradictory. The classical approach to specification, verification, and synthesis demands more detailed specifications that resolve any contradictions in the requirements. These detailed specifications are usually large, cumbersome, and hard to maintain or modify. In contrast, quantitative frameworks allow the formalization of the intuitive idea that what is desired is an implementation that comes "closest" to satisfying the mutually incompatible requirements, according to a measure of fit that can be defined by the requirements engineer. One flexible framework for quantifying how "well" an implementation satisfies a specification is offered by simulation distances that are parameterized by an error model. We introduce this framework, study its properties, and provide an algorithmic solution for the following quantitative synthesis question: given two (or more) behavioral requirements specified by possibly incompatible finite-state machines, and an error model, find the finite-state implementation that minimizes the maximal simulation distance to the given requirements. Furthermore, we generalize the framework to handle infinite alphabets (for example, realvalued domains). We also demonstrate how quantitative specifications based on simulation distances might lead to smaller and easier to modify specifications. Finally, we illustrate our approach using case studies on error correcting codes and scheduler synthesis.
AU - Cerny, Pavol
AU - Gopi, Sivakanth
AU - Henzinger, Thomas A
AU - Radhakrishna, Arjun
AU - Totla, Nishant
ID - 2890
T2 - Proceedings of the tenth ACM international conference on Embedded software
TI - Synthesis from incompatible specifications
ER -