Ripples at edges of blooming lilies and torn plastic sheets.

Ripples arise at edges of petals of blooming Lilium casablanca flowers and at edges of torn plastic sheets. In both systems, ripples are a consequence of excess length along the edge of a sheet. Through the use of time-lapse videos of blooming lilies and published images of torn plastic sheets, we find that ripples in both systems are well described by the scaling relationship a∝w(L-w), where a is amplitude, w is wavelength, and L is arc length. A phenomenological relationship previously reported for self-similar ripple patterns, namely ⟨a⟩∝⟨w⟩, can be recovered by assuming that buckling stress is constant. Excess length along petal edges can also influence their overall Gaussian curvature, such that petals invert from a cup shape to a saddle shape upon blooming. Previous simulations of these shape changes have assumed that petal thickness decreases at least quadratically. Here, we evaluate tomograms of several varieties of lily buds and find that this assumption is valid along the short axis of the buds, but not the long axis. A challenge of employing traditional tomography methods to measure petal thickness is that the sample is destroyed; a single bud cannot be followed through the entire blooming process. To address this challenge, we provide proof of principle that the nondestructive, label-free method of x-ray tomography produces high-contrast three-dimensional scans on time scales short enough to follow lily blooming.

SynMap2 and SynMap3D: web-based whole-genome synteny browsers.

SUMMARY: Current synteny visualization tools either focus on small regions of sequence and do not illustrate genome-wide trends, or are complicated to use and create visualizations that are difficult to interpret. To address this challenge, The Comparative Genomics Platform (CoGe) has developed two web-based tools to visualize synteny across whole genomes. SynMap2 and SynMap3D allow researchers to explore whole genome synteny patterns (across two or three genomes, respectively) in responsive, web-based visualization and virtual reality environments. Both tools have access to the extensive CoGe genome database (containing over 30 000 genomes) as well as the option for users to upload their own data. By leveraging modern web technologies there is no installation required, making the tools widely accessible and easy to use. AVAILABILITY AND IMPLEMENTATION: Both tools are open source (MIT license) and freely available for use online through CoGe ( https://genomevolution.org ). SynMap2 and SynMap3D can be accessed at http://genomevolution.org/coge/SynMap.pl and http://genomevolution.org/coge/SynMap3D.pl , respectively. Source code is available: https://github.com/LyonsLab/coge . CONTACT: ericlyons@email.arizona.edu. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Hashedcubes: Simple, Low Memory, Real-Time Visual Exploration of Big Data.

We propose Hashedcubes, a data structure that enables real-time visual exploration of large datasets that improves the state of the art by virtue of its low memory requirements, low query latencies, and implementation simplicity. In some instances, Hashedcubes notably requires two orders of magnitude less space than recent data cube visualization proposals. In this paper, we describe the algorithms to build and query Hashedcubes, and how it can drive well-known interactive visualizations such as binned scatterplots, linked histograms and heatmaps. We report memory usage, build time and query latencies for a variety of synthetic and real-world datasets, and find that although sometimes Hashedcubes offers slightly slower querying times to the state of the art, the typical query is answered fast enough to easily sustain a interaction. In datasets with hundreds of millions of elements, only about 2% of the queries take longer than 40ms. Finally, we discuss the limitations of data structure, potential spacetime tradeoffs, and future research directions.

Extracting Metrics for Three-dimensional Root Systems: Volume and Surface Analysis from In-soil X-ray Computed Tomography Data.

Plant roots play a critical role in plant-soil-microbe interactions that occur in the rhizosphere, as well as processes with important implications to climate change and crop management. Quantitative size information on roots in their native environment is invaluable for studying root growth and environmental processes involving plants. X-ray computed tomography (XCT) has been demonstrated to be an effective tool for in situ root scanning and analysis. We aimed to develop a costless and efficient tool that approximates the surface and volume of the root regardless of its shape from three-dimensional (3D) tomography data. The root structure of a Prairie dropseed (Sporobolus heterolepis) specimen was imaged using XCT. The root was reconstructed, and the primary root structure was extracted from the data using a combination of licensed and open-source software. An isosurface polygonal mesh was then created for ease of analysis. We have developed the standalone application imeshJ, generated in MATLAB(1), to calculate root volume and surface area from the mesh. The outputs of imeshJ are surface area (in mm(2)) and the volume (in mm(3)). The process, utilizing a unique combination of tools from imaging to quantitative root analysis, is described. A combination of XCT and open-source software proved to be a powerful combination to noninvasively image plant root samples, segment root data, and extract quantitative information from the 3D data. This methodology of processing 3D data should be applicable to other material/sample systems where there is connectivity between components of similar X-ray attenuation and difficulties arise with segmentation.