TY - JOUR
AB - The fact that a sum of isotropic Gaussian kernels can have more modes than kernels is surprising. Extra (ghost) modes do not exist in ℝ1 and are generally not well studied in higher dimensions. We study a configuration of n+1 Gaussian kernels for which there are exactly n+2 modes. We show that all modes lie on a finite set of lines, which we call axes, and study the restriction of the Gaussian mixture to these axes in order to discover that there are an exponential number of critical points in this configuration. Although the existence of ghost modes remained unknown due to the difficulty of finding examples in ℝ2, we show that the resilience of ghost modes grows like the square root of the dimension. In addition, we exhibit finite configurations of isotropic Gaussian kernels with superlinearly many modes.
AU - Edelsbrunner, Herbert
AU - Fasy, Brittany Terese
AU - Rote, Günter
ID - 2815
IS - 4
JF - Discrete & Computational Geometry
TI - Add isotropic Gaussian kernels at own risk: More and more resilient modes in higher dimensions
VL - 49
ER -
TY - JOUR
AB - Identification of genes that control root system architecture in crop plants requires innovations that enable high-throughput and accurate measurements of root system architecture through time. We demonstrate the ability of a semiautomated 3D in vivo imaging and digital phenotyping pipeline to interrogate the quantitative genetic basis of root system growth in a rice biparental mapping population, Bala x Azucena. We phenotyped >1,400 3D root models and >57,000 2D images for a suite of 25 traits that quantified the distribution, shape, extent of exploration, and the intrinsic size of root networks at days 12, 14, and 16 of growth in a gellan gum medium. From these data we identified 89 quantitative trait loci, some of which correspond to those found previously in soil-grown plants, and provide evidence for genetic tradeoffs in root growth allocations, such as between the extent and thoroughness of exploration. We also developed a multivariate method for generating and mapping central root architecture phenotypes and used it to identify five major quantitative trait loci (r2 = 24-37%), two of which were not identified by our univariate analysis. Our imaging and analytical platform provides a means to identify genes with high potential for improving root traits and agronomic qualities of crops.
AU - Topp, Christopher
AU - Iyer Pascuzzi, Anjali
AU - Anderson, Jill
AU - Lee, Cheng
AU - Zurek, Paul
AU - Symonova, Olga
AU - Zheng, Ying
AU - Bucksch, Alexander
AU - Mileyko, Yuriy
AU - Galkovskyi, Taras
AU - Moore, Brad
AU - Harer, John
AU - Edelsbrunner, Herbert
AU - Mitchell Olds, Thomas
AU - Weitz, Joshua
AU - Benfey, Philip
ID - 2822
IS - 18
JF - PNAS
TI - 3D phenotyping and quantitative trait locus mapping identify core regions of the rice genome controlling root architecture
VL - 110
ER -
TY - CONF
AB - Mathematical objects can be measured unambiguously, but not so objects from our physical world. Even the total length of tubelike shapes has its difficulties. We introduce a combination of geometric, probabilistic, and topological methods to design a stable length estimate for tube-like shapes; that is: one that is insensitive to small shape changes.
AU - Edelsbrunner, Herbert
AU - Pausinger, Florian
ID - 2843
T2 - 17th IAPR International Conference on Discrete Geometry for Computer Imagery
TI - Stable length estimates of tube-like shapes
VL - 7749
ER -
TY - JOUR
AB - Given a continuous function f:X-R on a topological space, we consider the preimages of intervals and their homology groups and show how to read the ranks of these groups from the extended persistence diagram of f. In addition, we quantify the robustness of the homology classes under perturbations of f using well groups, and we show how to read the ranks of these groups from the same extended persistence diagram. The special case X=R3 has ramifications in the fields of medical imaging and scientific visualization.
AU - Bendich, Paul
AU - Edelsbrunner, Herbert
AU - Morozov, Dmitriy
AU - Patel, Amit
ID - 2859
IS - 1
JF - Homology, Homotopy and Applications
TI - Homology and robustness of level and interlevel sets
VL - 15
ER -
TY - JOUR
AB - Root system growth and development is highly plastic and is influenced by the surrounding environment. Roots frequently grow in heterogeneous environments that include interactions from neighboring plants and physical impediments in the rhizosphere. To investigate how planting density and physical objects affect root system growth, we grew rice in a transparent gel system in close proximity with another plant or a physical object. Root systems were imaged and reconstructed in three dimensions. Root-root interaction strength was calculated using quantitative metrics that characterize the extent towhich the reconstructed root systems overlap each other. Surprisingly, we found the overlap of root systems of the same genotype was significantly higher than that of root systems of different genotypes. Root systems of the same genotype tended to grow toward each other but those of different genotypes appeared to avoid each other. Shoot separation experiments excluded the possibility of aerial interactions, suggesting root communication. Staggered plantings indicated that interactions likely occur at root tips in close proximity. Recognition of obstacles also occurred through root tips, but through physical contact in a size-dependent manner. These results indicate that root systems use two different forms of communication to recognize objects and alter root architecture: root-root recognition, possibly mediated through root exudates, and root-object recognition mediated by physical contact at the root tips. This finding suggests that root tips act as local sensors that integrate rhizosphere information into global root architectural changes.
AU - Fang, Suqin
AU - Clark, Randy
AU - Zheng, Ying
AU - Iyer Pascuzzi, Anjali
AU - Weitz, Joshua
AU - Kochian, Leon
AU - Edelsbrunner, Herbert
AU - Liao, Hong
AU - Benfey, Philip
ID - 2887
IS - 7
JF - PNAS
TI - Genotypic recognition and spatial responses by rice roots
VL - 110
ER -
TY - CONF
AB - We introduce the M-modes problem for graphical models: predicting the M label configurations of highest probability that are at the same time local maxima of the probability landscape. M-modes have multiple possible applications: because they are intrinsically diverse, they provide a principled alternative to non-maximum suppression techniques for structured prediction, they can act as codebook vectors for quantizing the configuration space, or they can form component centers for mixture model approximation. We present two algorithms for solving the M-modes problem. The first algorithm solves the problem in polynomial time when the underlying graphical model is a simple chain. The second algorithm solves the problem for junction chains. In synthetic and real dataset, we demonstrate how M-modes can improve the performance of prediction. We also use the generated modes as a tool to understand the topography of the probability distribution of configurations, for example with relation to the training set size and amount of noise in the data.
AU - Chen, Chao
AU - Kolmogorov, Vladimir
AU - Yan, Zhu
AU - Metaxas, Dimitris
AU - Lampert, Christoph
ID - 2901
TI - Computing the M most probable modes of a graphical model
VL - 31
ER -
TY - CONF
AB - Motivated by an application in cell biology, we describe an extension of the kinetic data structures framework from Delaunay triangulations to fixed-radius alpha complexes. Our algorithm is implemented
using CGAL, following the exact geometric computation paradigm. We report on several
techniques to accelerate the computation that turn our implementation applicable to the underlying biological
problem.
AU - Kerber, Michael
AU - Edelsbrunner, Herbert
ID - 2906
T2 - 2013 Proceedings of the 15th Workshop on Algorithm Engineering and Experiments
TI - 3D kinetic alpha complexes and their implementation
ER -
TY - JOUR
AB - In this paper, we present the first output-sensitive algorithm to compute the persistence diagram of a filtered simplicial complex. For any Γ > 0, it returns only those homology classes with persistence at least Γ. Instead of the classical reduction via column operations, our algorithm performs rank computations on submatrices of the boundary matrix. For an arbitrary constant δ ∈ (0, 1), the running time is O (C (1 - δ) Γ R d (n) log n), where C (1 - δ) Γ is the number of homology classes with persistence at least (1 - δ) Γ, n is the total number of simplices in the complex, d its dimension, and R d (n) is the complexity of computing the rank of an n × n matrix with O (d n) nonzero entries. Depending on the choice of the rank algorithm, this yields a deterministic O (C (1 - δ) Γ n 2.376) algorithm, an O (C (1 - δ) Γ n 2.28) Las-Vegas algorithm, or an O (C (1 - δ) Γ n 2 + ε{lunate}) Monte-Carlo algorithm for an arbitrary ε{lunate} > 0. The space complexity of the Monte-Carlo version is bounded by O (d n) = O (n log n).
AU - Chen, Chao
AU - Kerber, Michael
ID - 2939
IS - 4
JF - Computational Geometry: Theory and Applications
TI - An output sensitive algorithm for persistent homology
VL - 46
ER -
TY - CONF
AB - A straight skeleton is a well-known geometric structure, and several algorithms exist to construct the straight skeleton for a given polygon or planar straight-line graph. In this paper, we ask the reverse question: Given the straight skeleton (in form of a planar straight-line graph, with some rays to infinity), can we reconstruct a planar straight-line graph for which this was the straight skeleton? We show how to reduce this problem to the problem of finding a line that intersects a set of convex polygons. We can find these convex polygons and all such lines in $O(nlog n)$ time in the Real RAM computer model, where $n$ denotes the number of edges of the input graph. We also explain how our approach can be used for recognizing Voronoi diagrams of points, thereby completing a partial solution provided by Ash and Bolker in 1985.
AU - Biedl, Therese
AU - Held, Martin
AU - Huber, Stefan
ID - 2209
TI - Recognizing straight skeletons and Voronoi diagrams and reconstructing their input
ER -
TY - CONF
AB - A straight skeleton is a well-known geometric structure, and several algorithms exist to construct the straight skeleton for a given polygon. In this paper, we ask the reverse question: Given the straight skeleton (in form of a tree with a drawing in the plane, but with the exact position of the leaves unspecified), can we reconstruct the polygon? We show that in most cases there exists at most one polygon; in the remaining case there is an infinite number of polygons determined by one angle that can range in an interval. We can find this (set of) polygon(s) in linear time in the Real RAM computer model.
AU - Biedl, Therese
AU - Held, Martin
AU - Huber, Stefan
ID - 2210
T2 - 29th European Workshop on Computational Geometry
TI - Reconstructing polygons from embedded straight skeletons
ER -