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9,882 results for “Scale”
Figure 7 in A new scale insect host family (Hemiptera: Asterolecaniidae) for Aphytis (Hymenoptera: Aphelinidae) in China
Figure 7. Diaspidid scale Chrysomphalus aonidum and its parasitoid Aphytis holoxanthus. (a) C. aonidum; (b) a larva of A. holoxanthus on the scale body; (c) mature pupa of A. holoxanthus, with meconial pellets; (d) 2 mature pupae of A. holoxanthus, with meconial pellets; (e) 3 mature pupae of A. holoxanthus, with meconial pellets; (f) 4 mature pupae of A. holoxanthus, with meconial pellets.
Characterization of large-scale structural variants using Linked-Reads
<p>Here we propose novel algorithms to characterize large (>40 Kbp) interspersed segmental duplications, (> 80 Kbp) inversions, (> 100 Kbp) deletions, and (> 100 Kbp) translocations using Linked-Read sequencing data. Linked-Read sequencing provides long range information, where Illumina reads are tagged with barcodes that can be used to assign short reads to pools of larger (30-50 Kbp) molecules.</p> <p><br> Our methods rely on split molecule sequence signature that we have previously described. Similar to the split read, split molecules refer to large segments of DNA that span an SV breakpoint. Therefore, when mapped to the reference genome, the mapping of these segments would be discontinuous.</p> <p><br> We redesign our earlier algorithm, VALOR, to specifically leverage Linked-Read sequencing data to discover large <br> structural variation. We implement our new algorithms in a new software package, called VALOR2. </p>
Dataset - Large-scale kinetic metabolic models of Pseudomonas putida KT2440 for consistent design of metabolic engineering strategies
<p>Models developed for the manuscript “Large-scale kinetic metabolic models of<em> Pseudomonas putida</em> for consistent design of metabolic engineering strategies" by M. Tokic, V. Hatzimanikatis, and L. Miskovic.</p> <ul> <li>Thermodynamically curated and gap-filled genome-scale model of <em>P. putida</em> iJN1411, iJN1411cur. <ul> <li>CuratediJN1411GEM.mat</li> </ul> </li> <li>Three systematically reduced stoichiometric models of <em>P. putida</em>: <ul> <li>D1 model, RedModelD1SminP2.mat</li> <li>D2 model, RedModelD2SminP2.mat - used for the studies performed in the manuscript</li> <li>D3 model, RedModelD3SminP2.mat</li> </ul> </li> </ul> <p> </p>
FIGURES 1–6. Quwatanabius chiaw, male specimen. 1. habitus, scale bar represents 1 in Taxonomic notes on the genus Quwatanabius in Taiwan (Coleoptera: Staphylinidae)
FIGURES 1–6. Quwatanabius chiaw, male specimen. 1. habitus, scale bar represents 1mm; 2. male sternite VIII; 3. male sternite IX; 4. male tergite X; 5. line drawing of aedeagus in lateral view; 6. line drawing of aedeagus in ventral view.
Brilliant angle independent structural colours preserved in weevil scales from the Swiss Pleistocene
<p>Raw SAXS detector image and Microspectrophotometric data for "Brilliant angle independent structural colours preserved in weevil scales from the Swiss Pleistocene"</p>
Modeling of the potential distribution of Eichhornia crassipes on a global scale: risks and threats to water ecosystems. Supplementary material
<p>https://doi.org/10.4136/1980-993X</p>
Global-scale characterization of turning points in arid and semi-arid ecosystem functioning
<p>Data accompanying the paper:</p> <p>Bernardino, P., De Keersmaecker, W., Fensholt, R., Verbesselt, J., Somers, B. and Horion, S. 2020. Global-scale characterization of turning points in arid and semi-arid ecosystem functioning.</p>
Pairwise distance demarcation of species in the family Coronaviridae. a, Diagonal matrix of PPDs of 2,505 viruses clustered according to 49 coronavirus species, 39 established and 10 pending or tentative, and ordered from the most to least populous species, from left to right; green and white, PPDs smaller and larger than the inter-species threshold, respectively. Areas of the green squares along the diagonal are proportional to the virus sampling of the respective species, and virus prototypes of the five most sampled species are specified to the left; asterisks indicate species that include viruses whose intra-species PPDs crossed the inter-species threshold (threshold 'violators'). b, Maximal intra-species PPDs (x axis, linear scale) plotted against virus sampling (y axis, log scale) for 49 species (green dots) of the Coronaviridae. Indicated are the acronyms of virus prototypes of the seven most sampled species. Green and blue plot sections represent intra-species and intra-subgenera PPD ranges. The vertical black line indicates the inter-species threshold. c, Shown are the PDs of non-identical residues (y axis) for four viruses representing three major phylogenetic lineages (clades) of the species Severe acute respiratorysyndrome-related coronavirus (panel b) and all pairs of the 256 viruses of this species ('all pairs'). The PD values were derived from pairwise distances in the MSA that were calculated using an identity matrix. Panels a and b were adopted from the DEmARC v.1.4 output. in The species Severe acute respiratory syndromerelated coronavirus: classifying 2019-nCoV and naming it SARS-CoV-2
Pairwise distance demarcation of species in the family Coronaviridae. a, Diagonal matrix of PPDs of 2,505 viruses clustered according to 49 coronavirus species, 39 established and 10 pending or tentative, and ordered from the most to least populous species, from left to right; green and white, PPDs smaller and larger than the inter-species threshold, respectively. Areas of the green squares along the diagonal are proportional to the virus sampling of the respective species, and virus prototypes of the five most sampled species are specified to the left; asterisks indicate species that include viruses whose intra-species PPDs crossed the inter-species threshold (threshold 'violators'). b, Maximal intra-species PPDs (x axis, linear scale) plotted against virus sampling (y axis, log scale) for 49 species (green dots) of the Coronaviridae. Indicated are the acronyms of virus prototypes of the seven most sampled species. Green and blue plot sections represent intra-species and intra-subgenera PPD ranges. The vertical black line indicates the inter-species threshold. c, Shown are the PDs of non-identical residues (y axis) for four viruses representing three major phylogenetic lineages (clades) of the species Severe acute respiratorysyndrome-related coronavirus (panel b) and all pairs of the 256 viruses of this species ('all pairs'). The PD values were derived from pairwise distances in the MSA that were calculated using an identity matrix. Panels a and b were adopted from the DEmARC v.1.4 output.
MitoFinder: efficient automated large-scale extraction of mitogenomic data in target enrichment phylogenomics
<p><strong>MitoFinder: efficient automated large-scale extraction of mitogenomic data in target enrichment phylogenomics</strong></p> <p>Rémi Allio<sup>1</sup>, Alex Schomaker-Bastos<sup>2,†</sup>, Jonathan Romiguier<sup>1</sup>, Francisco Prosdocimi<sup>2</sup>, Benoit Nabholz<sup>1</sup>, and Frédéric Delsuc<sup>1</sup></p> <p><sup>1</sup><em>Institut des Sciences de l’Evolution de Montpellier (ISEM), CNRS, EPHE, IRD, Université de Montpellier, Montpellier, France.</em></p> <p><sup>2</sup><em>Laboratório Multidisciplinar para Análise de Dados (LAMPADA), Instituto de Bioquímica Médica Leopoldo de Meis, Universidade Federal do Rio de Janeiro, Rio de Janeiro, Brasil.</em></p> <p><sup>†</sup><em> In Memoriam (08/01/2015) </em></p> <p> </p> <p><em><strong>Correspondence</strong></em></p> <p>Rémi Allio</p> <p>Email: <a href="mailto:remi.allio@umontpelier.fr">remi.allio@umontpellier.fr</a></p> <p>Frédéric Delsuc</p> <p>Email: <a href="mailto:frederic.delsuc@umontpellier.fr">frederic.delsuc@umontpellier.fr</a></p> <p> </p> <p><strong><em>Running head</em></strong></p> <p>Mitochondrial signal from UCE capture data</p> <p> </p> <p><strong>Abstract</strong><strong> </strong></p> <p>Thanks to the development of high-throughput sequencing technologies, target enrichment sequencing of nuclear ultraconserved DNA elements (UCEs) now allows routinely inferring phylogenetic relationships from thousands of genomic markers. Recently, it has been shown that mitochondrial DNA (mtDNA) is frequently sequenced alongside the targeted loci in such capture experiments. Despite its broad evolutionary interest, mtDNA is rarely assembled and used in conjunction with nuclear markers in capture-based studies. Here, we developed MitoFinder, a user-friendly bioinformatic pipeline, to efficiently assemble and annotate mitogenomic data from hundreds of UCE libraries. As a case study, we used ants (Formicidae) for which 501 UCE libraries have been sequenced whereas only 29 mitogenomes are available. We compared the efficiency of four different assemblers (IDBA-UD, MEGAHIT, MetaSPAdes, and Trinity) for assembling both UCE and mtDNA loci. Using MitoFinder, we show that metagenomic assemblers, in particular MetaSPAdes, are well suited to assemble both UCEs and mtDNA. Mitogenomic signal was successfully extracted from all 501 UCE libraries allowing confirming species identification using COI barcoding. Moreover, our automated procedure retrieved 296 cases in which the mitochondrial genome was assembled in a single contig, thus increasing the number of available ant mitogenomes by an order of magnitude. By leveraging the power of metagenomic assemblers, MitoFinder provides an efficient tool to extract complementary mitogenomic data from UCE libraries, allowing testing for potential mito-nuclear discordance. Our approach is potentially applicable to other sequence capture methods, transcriptomic data, and whole genome shotgun sequencing in diverse taxa.</p> <p> </p> <p><strong><em>Figures & Tables</em></strong></p> <p><strong>Figure 1.</strong> Conceptualization of the pipeline used to assemble and extract UCE and mitochondrial signal from ultraconserved element sequencing data.</p> <p><strong>Figure 2</strong>. Comparison of the efficiency of the assemblers in terms of: A) computational time, B) number of potentially mitochondrial contigs identified, and C) number of mitochondrial genes annotated. Violin plots reflect the data distribution with a horizontal line indicating the median. Note that for the three metagenomic assemblers, 5 CPUs were used compared to 35 CPUs for Trinity. Plots were obtained using PlotsOfData (Postma & Goedhart 2019).</p> <p><strong>Figure 3.</strong> Phylogenomic relationships of ants (Formicidae). AA) Mito-nuclear phylogenetic differences among subfamily relationships based on the UCE and mtDNA supermatrices obtained with the assembler MetaSPAdes assembler. Clades corresponding to subfamilies were collapsed. Inter-subfamily relationships with UFBS < 95% were collapsed. Non-maximal node support values are reported. B) The topology obtained reflects the results of phylogenetic analyses based on the amino acid mitochondrial supermatrix (using MetaSPAdes as assembler). Histograms reflect the percent of UCEs (light grey) and mitochondrial genes (dark grey) recovered for each species. Illustrative pictures (*): <em>Diacamma sp</em>. (Ponerinae; top left), <em>Formica sp</em>. (Formicinae; top right), and <em>Messor barbarus </em>(Myrmicinae; bottom right).</p> <p><strong>Table 1. </strong>Summary statistics on assembly results according to the assembler used. The values are averages over the 501 assemblies, except for the assembly time, which is a median value. The two tables report specific statistics for A) ultraconserved elements data, and B) mitochondrial data. Note that 35 CPUs were used for Trinity whereas 5 CPUs were used for other assemblers.</p> <p><strong>Table 2.</strong> Statistical comparison between the performances of the different assemblers. Statistical significance was estimated with a paired non parametric test (paired wilcoxon test). *** = <em>p</em><0.001; ** = <em>p</em><0.01; * = <em>p</em><0.05; NS = <em>p</em>>0.05; and (+)/(-) is the result of the comparison between the row and the column.</p> <p> </p> <p><strong><em>Appendices</em></strong></p> <p><strong>Appendix S1.</strong> List of the 501 UCE libraries (SRA accessions) and associated metadata.</p> <p><strong>Appendix S2.</strong> Summary statistics on mitochondrial signal recovered per species and depending on the assembler used. The table provides the number of contigs and genes recovered with MitoFinder and the size of each annotated gene.</p> <p><strong>Appendix S3.</strong> Summary statistics of barcoding analyses. Detailed results for both BOLDsystem and Megablast analyses are provided for each CO1 recovered with MitoFinder using MetaSPAdes.</p> <p><strong>Appendix S4.</strong> Detailed results of tree distance analyses realized with Dquad (Ranwez, Criscuolo, & Douzery 2010). Trees obtained with each assembler with mitochondrial amino acid supermatrix, mitochondrial nucleotide supermatrix, and UCE nucleotide supermatrix were compared with each others.</p> <p><strong>Appendix S5</strong>. List of Genbank accession numbers for newly generated mitchondrial contigs.</p> <p> </p> <p><strong><em>Zenodo supplementary files</em></strong></p> <p><strong>Assembly_results.tar.gz</strong> Contains all contigs obtained for each species with the different assemblers implemented in MitoFinder.</p> <p><strong>MitoFinder_annotations.tar.gz</strong> Contains MitoFinder annotations for each species. (based on the contigs obtained with MetaSPAdes)</p> <p><strong>UCE_results.tar.gz</strong> Contains all annotated UCE obtained for each species after UCE identification with PHYLUCE. (MetaSPAdes)</p> <p><strong>Final_mtDNA_alignments.tar.gz</strong> Contains the final mitochondrial gene alignments. (MetaSPAdes)</p> <p><strong>Final_UCE_alignments.tar.gz</strong> Contains the final UCE alignments. (MetaSPAdes)</p> <p><strong>Final_mtDNA_matrices.tar.gz</strong> Contains the final mi tochondrial supermatrices (AA and NT) used for the phylogenetic analyses. (MetaSPAdes)</p> <p><strong>Metaspades_final_UCE_matrix.phy</strong> The final UCE supermatrix used for the phylogenetic analyses. (MetaSPAdes)</p>
Replication package for "Mutation testing of smart contracts at scale"
<p>Replication package for TAP2020 paper "Mutation testing of smart contracts at scale"</p> <p>Abstract: It is crucial that smart contracts are tested thoroughly due to their immutable nature. Even small bugs in smart contracts can lead to huge monetary losses. However, testing is not enough; it is also important to ensure the quality and completeness of the tests. There are already several approaches that tackle this challenge with mutation testing, but their effectiveness is questionable since they only considered small contract samples. Hence, we evaluate the quality of smart contract mutation testing at scale. We choose the most promising of the existing (smart contract specific) mutation operators, analyse their effectiveness in terms of killability and highlight severe vulnerabilities that can be injected with the mutations. Moreover, we improve the existing mutation methods by introducing a novel killing condition that is able to detect a deviation in the gas consumption, i.e., in the monetary value that is required to perform transactions.</p>
On Strong Scaling and Open Source Tools for Analyzing Atom Probe Tomography Data
<p>This repository contains supplemental results to the paper "On Strong Scaling and Open Source Tools<br> for Analyzing Atom Probe Tomography Data".</p> <p>Specifically, the input parameter and result files from all synthetic benchmark studies.<br> The results file for all synthetic specimen benchmark studies are available from the<br> authors upon serious request.</p> <p><strong>The repository content is as follows:</strong></p> <p><strong>Real world data:<br> Three triplets of *.tar.gz archive files document the settings and analysis files for the real world case studies</strong><br> 3013902 is the incipient specimen,<br> 2763207 the intermediate specimen, and<br> 3345501 the mature specimen.</p> <p><strong>Scripts.zip</strong><br> Contains all batch scripts we used for performing the analyses as a queue</p> <p><strong>Synthetic data:</strong></p> <p><strong>APTCrystallography.zip</strong><br> Contains all results from the benchmarking of the reimplemented Vicente Araullo-Peters et al. method</p> <p><strong>FullVolumeTessellation.zip</strong><br> Contains all results from the benchmarking of the Voro++ Voronoi volume tessellation method except for the HDF5/XDMF volume tessellation files of the 200 and 2000 million ion datasets</p> <p><strong>TwoPointStatistics.zip</strong><br> Contains all results from benchmarking the computing of 2-point spatial statistics</p> <p><strong>TipSurfaceDescrSpatialStatistics.zip</strong><br> Contains all results from benchmarking the alpha shape computation, descriptive spatial statistics, and clustering analyses</p> <p><strong>PARAPROBE.Results.2Mio.tar.gz<br> PARAPROBE.Results.20Mio.tar.gz</strong><br> <strong>PARAPROBE.Results.200Mio.tar.gz</strong><br> Contains all settings files and some results from benchmarking the hybrid implementation.</p> <p><strong>Unpack the individual repositories using tar through Linux console as follows:</strong><br> tar -xvf <archivename> <br> where <archivename> is a placeholder for the respective tar gz compressed archives within the ZIP file.<br> Alternatively WinRAR can be used on a Windows system.</p> <p><strong>We would kindly like to ask you to use the following repository<br> to access source code of PARAPROBE in the future:</strong></p> <p><strong>https://gitlab.mpcdf.mpg.de/mpie-aptfim-toolbox/paraprobe<br> https://paraprobe-toolbox.readthedocs.io/en/latest/</strong><br> <br> <strong>Only above repository will be updated in the future! </strong><br> <strong>Only there new code additions and bugfixes are posted!<br> The examples folder of this repository contains a folder examples/tasks/paper14 which shows how<br> to run a workflow of paraprobe tools from this above repository to run analyses akin as reported in this paper.</strong></p> <p>Recommendations and bug reports to M. Kühbach are appreciated! Happy APT analyzing!</p> <p>------------------------------------------------------------------------------------------------------------------------------------------------------------------------<br> <strong>The PARAPROBE source code version we used for analyzing the synthetic and real world APT<br> specimens in the paper used an earlier development version of the PARAPROBE tool, the source code</strong><br> <strong>is here:</strong></p> <p>PARAPROBE_20190117_VersionUsedForPaper.zip</p> <p>https://github.com/mkuehbach/PARAPROBE<br> https://paraprobe.readthedocs.io/en/latest/</p> <p> </p>
FIGURE 3. Median predorsal scales of Siphamia guttulata (A—paralectotype, AMS I.16306-001, 25.7 mm SL; B—CSIRO H 7457-01, 27 mm SL) and Siphamia tubifer (C—CSIRO H 6752-02, 31 mm SL). Scale bar = 0.5 mm. Yellow arrows point to first dorsal spine, numbers or pink arrows indicate median predorsal scales. Fifth median predorsal scale of Fig. C is a scale pocket as the scale has been lost. in Redescription and distributional range extension of the Speckled Siphonfish, Siphamia guttulata (Pisces: Apogonidae)
FIGURE 3. Median predorsal scales of Siphamia guttulata (A—paralectotype, AMS I.16306-001, 25.7 mm SL; B—CSIRO H 7457-01, 27 mm SL) and Siphamia tubifer (C—CSIRO H 6752-02, 31 mm SL). Scale bar = 0.5 mm. Yellow arrows point to first dorsal spine, numbers or pink arrows indicate median predorsal scales. Fifth median predorsal scale of Fig. C is a scale pocket as the scale has been lost.
FIGURE2. Digital radiograph of Siphamia guttulata (CSIRO H 6648-02, 25 mm SL). Blue circle highlighting two supraneurals. Scale bar = 0.5 mm. in Redescription and distributional range extension of the Speckled Siphonfish, Siphamia guttulata (Pisces: Apogonidae)
FIGURE2. Digital radiograph of Siphamia guttulata (CSIRO H 6648-02, 25 mm SL). Blue circle highlighting two supraneurals. Scale bar = 0.5 mm.
FIGURE 90 in A review of neococcid scale insects (Hemiptera: Sternorrhyncha: Coccomorpha) based on the morphology of the adult males
FIGURE 90. Cardiococcus major (Maskell). Macropterous male. (Coccidae). Where A=cranial apophysis and R=dermal reticulations on ocular sclerite.
FIGURE 87 in A review of neococcid scale insects (Hemiptera: Sternorrhyncha: Coccomorpha) based on the morphology of the adult males
FIGURE 87. Parthenolecanium persicae (Fabricius). Macropterous male. (Coccidae). Where A=cranial apophysis, D=fleshy seta, E=hair-like seta, and R=dermal reticulations on ocular sclerite.
FIGURE 86 in A review of neococcid scale insects (Hemiptera: Sternorrhyncha: Coccomorpha) based on the morphology of the adult males
FIGURE 86. Rhodesaclerda insleyae Hodgson & Millar. Macropterous male. (Aclerdidae, Rhodesaclerdinae). Where D=simple pore and R=dermal reticulations on ocular sclerite.
FIGURE 83 in A review of neococcid scale insects (Hemiptera: Sternorrhyncha: Coccomorpha) based on the morphology of the adult males
FIGURE 83. Aclerda sp. B. South Dakota, USA. Macropterous male. (Aclerdidae, Aclerdinae). Where A=cranial apophysis, C=loculate pore, D=simple pore and R=dermal reticulations on ocular sclerite.
FIGURE 81 in A review of neococcid scale insects (Hemiptera: Sternorrhyncha: Coccomorpha) based on the morphology of the adult males
FIGURE 81. Aclerda tokionis Cockerell. Macropterous male. (Aclerdidae, Aclerdinae). Where A=cranial apophysis.
FIGURE 79 in A review of neococcid scale insects (Hemiptera: Sternorrhyncha: Coccomorpha) based on the morphology of the adult males
FIGURE 79. Aclerda distorta Green. Macropterous male. (Aclerdidae, Aclerdinae). Where A=cranial apophysis, E=loculate pore and R=dermal reticulations on ocular sclerite.
FIGURE 77 in A review of neococcid scale insects (Hemiptera: Sternorrhyncha: Coccomorpha) based on the morphology of the adult males
FIGURE 77. Micrococcus bodenheimeri Bytinski-Salz. Apterous adult male. (Micrococcidae) (After Miller & Williams 1995). Where B=small bilocular pores, C=discoidal pores and D=large bilocular pores.
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.