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3,878 results for “Molecular data”
Fig. 3 in Heterophyid trematodes (Digenea) from penguins: A new species of Ascocotyle Looss, 1899, first description of metacercaria of Ascocotyle (A.) patagoniensis Hernández-Orts, Montero, Crespo, García, Raga and Aznar, 2012, and first molecular data
Fig. 3. Ascocotyle (Phagicola) cameliae n. sp. from the intestine of Spheniscus magellanicus collected in Patagonia, Argentina. (A–D) Anterior end with circumoral spines; note variation in spine number, 22 spines (A and B), 19 spines (C) and 24 spines (D). (E) Terminal genitalia, ventral view of paratype (IPCAS D-805).
Fig. 1 in Heterophyid trematodes (Digenea) from penguins: A new species of Ascocotyle Looss, 1899, first description of metacercaria of Ascocotyle (A.) patagoniensis Hernández-Orts, Montero, Crespo, García, Raga and Aznar, 2012, and first molecular data
Fig. 1. Ascocotyle (Phagicola) cameliae n. sp. from the intestine of Spheniscus magellanicus collected in Patagonia, Argentina. (A) Total, ventral view of holotype (MLPHe 7501). (B) Total, dorsal view of paratype (IPCAS D-805).
Fig. 2 in Heterophyid trematodes (Digenea) from penguins: A new species of Ascocotyle Looss, 1899, first description of metacercaria of Ascocotyle (A.) patagoniensis Hernández-Orts, Montero, Crespo, García, Raga and Aznar, 2012, and first molecular data
Fig. 2. Ascocotyle (Phagicola) cameliae n. sp. from the intestine Spheniscus magellanicus collected in Patagonia, Argentina. Scanning electron micrographs. (A and B) Total, ventral view. (C and D). Anterior end, apical view. (E). Anterior end, ventral view.
Fig. 6 in Heterophyid trematodes (Digenea) from penguins: A new species of Ascocotyle Looss, 1899, first description of metacercaria of Ascocotyle (A.) patagoniensis Hernández-Orts, Montero, Crespo, García, Raga and Aznar, 2012, and first molecular data
Fig. 6. Bayesian inference (BI) phylogram based on the partial (D1–D3 domains) sequences of 28S rDNA for the species of Ascocotyle. Posterior probability values are given above the branches. Support values with <0.95 posterior probability are omitted. The branch length scale-bar indicates the expected number of substitutions per site. The newly-generated sequences are colour indicated (in blue) and highlighted in bold. The outgroup is represented in grey colour. Host origins of the specimens sequenced are symbol indicated on the tree. (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)
Fig. 4 in A new distribution record of Chrysosplenium grayanum Maxim. (Saxifragaceae) in Korea: Evidence from morphological and molecular data
Fig. 4. Phylogenetic relationships resulting from the maximum parsimony analysis of nrITS sequences from eight Chrysosplenium taxa and two outgroup taxa (C. flagelliferaum in ser. Flagellifera and C. japonicum in ser. Alternifolia). Numbers above the branches indicate bootstrap values (≧80) for maximum parsimony (left) and neighbor-joining (right) analysis.
Fig. 2 in A new distribution record of Chrysosplenium grayanum Maxim. (Saxifragaceae) in Korea: Evidence from morphological and molecular data
Fig. 2. Photos of Chrysosplenium grayanum Maxim. A. Plant habit during flowering; B. Leaves; C. Inflorescence with bracteal leaves; D. Close-up of sepals and stamens.
Fig. 3 in A new distribution record of Chrysosplenium grayanum Maxim. (Saxifragaceae) in Korea: Evidence from morphological and molecular data
Fig. 3. Scanning electron micrograph of seed of Chysosplenium grayanum Maxim. A. Seed; B. Close-up of seed surface, showing smooth surface with cylindrical papillose with roundish head at the tip.
Fig. 1 in A new distribution record of Chrysosplenium grayanum Maxim. (Saxifragaceae) in Korea: Evidence from morphological and molecular data
Fig. 1. Illustrations of Chrysosplenium grayanum Maxim. A. Flowering plant; B. Inflorescence; C. Sepals and stamens; D. Capsule with persistent sepals; E. Leaf arrangement. Illustrations of Chrysosplenium grayanum were drawn by Park Chan-Ae.
Fig. 5 in Phylogeography and potential glacial refugia of terrestrial gastropod Faustina faustina (Rossmässler, 1835) (Gastropoda: Eupulmonata: Helicidae) inferred from molecular data and species distribution models
Fig. 5 BEAST phylogenetic tree based on the COI sequences. Node values indicate divergence estimated in MYA
Fig. 7 in Phylogeography and potential glacial refugia of terrestrial gastropod Faustina faustina (Rossmässler, 1835) (Gastropoda: Eupulmonata: Helicidae) inferred from molecular data and species distribution models
Fig. 7 Areas of climatic stability over time periods from the LGM through the present, based on summed climatic suitability models for the LGM, mid-Holocene, and present day for three differed GCMs. Stability increase from red to yellow color. White-filled areas show the
Data and code for behavioral analysis of: Structural and Molecular Properties of Insect Type II Motor Axon Terminals.
<p>Data and code for behavioral analysis of: Structural and Molecular Properties of Insect Type II Motor Axon Terminals.</p> <p>v1.2: typos corrected and all files available in a single .zip file for download</p>
Data File for Manuscript "Comprehensive Molecular Simulation on Triple Negative Breast Cancer Transcriptomics Features of mir-145 and 3' UTR of ARF6 mRNA"
<p>This is a data file for the manuscript "Comprehensive Molecular Simulation on Triple Negative Breast Cancer Transcriptomics Features of mir-145 and 3’ UTR of ARF6 mRNA". It comprises of molecular docking (AUTODOCK VINA 4) and dynamics data (NAMD and VMD).</p>
Partitioned Image Data for Machine Learning Analysis of Molecular Biology Figures
<p><strong> Corpus Composition</strong></p> <p>This data collection provides four types of hand-curated images from open access research articles images. The types are:</p> <ol> <li>chart (n=811): data displays such as bar charts, scatterplots, line graphs, etc.</li> <li>diagram (n=816): any general conceptual diagram</li> <li>gel (n=1182): the output of electrophoresis experiments in Northern, Western, or Southern Blot experiments. </li> <li>histology (n=3458): microscope images of tissue with histological staining</li> </ol> <p>The images are simply organized in subdirectories as individual files. File names are based on PubMed Id and Figure number. </p>
Data For New Methods for Understanding and Controlling the Self-Assembly of Reacting Systems Using Coarse-Grained Molecular Dynamics
<p>Data necessary to reproduce results in the dissertation : Thomas, Stephen, "New Methods for Understanding and Controlling the Self-Assembly of Reacting Systems Using Coarse-Grained Molecular Dynamics" (2018). <em>Boise State University Theses and Dissertations</em>. 1448.</p> <p>10.18122/td/1448/boisestate</p>
Supplementary data for "Molecular-scale thermally activated fractures in methane hydrates: A molecular dynamics study"
<p>In this dataset you can find</p> <p>- a data sample that can be used to confirm the plots in the paper. This can be found in the folder "data_sample". Each folder inside "data_sample" is one simulation. It contains the thermodynamic output from the simulation (log.lammps), and the input script (mw_hydrate_pennycrack.in) and input data (s1_unit_cell_mw.data and water_methane_hydrate.sw) that enables rerunning the simulation using LAMMPS.</p> <p>- A custom LAMMPS region, region_ellipsoid. This has to be compiled into LAMMPS in order to create the systems that we simulate.</p> <p>- A python script, plot_data.py, that shows how to extract the relevant data from the lammps log files, which enables the partial reproduction of figure 3 in the paper. See instructions below for requirements to use this script.</p> <p> </p> <p>"region_ellipsoid" and "data_sample" are in zip containers. In order to use them, please unzip them and leave the resulting folders in the same directory as this README file.</p> <p> </p> <p>Installation instructions to make "plot_data.py" work (assuming you already have numpy and matplotlib):</p> <p>> pip3 install git+https://github.com/henriasv/regex-file-collector.git</p> <p>> pip3 install git+https://github.com/henriasv/lammps-logfile.git</p> <p> </p> <p>If this does not work, please contact Henrik Andersen Sveinsson, henriasv@fys.uio.no</p>
Fig. 4 in Molecular prevalence and phylogenetic relationship of Haemoproteus and Plasmodium parasites of owls in Thailand: Data from a rehabilitation centre
Fig. 4. Colour heatmap of pairwise genetic distances estimated from nucleotide sequences of the cytochrome b gene (479 bp) of Haemoproteus spp. based on the Jukes-Canter model. (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)
Fig. 3 in Molecular prevalence and phylogenetic relationship of Haemoproteus and Plasmodium parasites of owls in Thailand: Data from a rehabilitation centre
Fig. 3. Bayesian phylogeny based on partial cytochrome b gene (479 base pairs) of Haemoproteus species lineages. The lineages reported in this study are given in bold. MalAvi lineage codes and GenBank accession numbers are given after species names. Node values (in percentages) indicate posterior clade probabilities. Vertical bars indicate clades of Haemoproteus subgenus (A), Parahaemoproteus (B). Almost all of the Parahaemoproteus lineages recovered from owls were grouped together (clade B-1, grey box). * indicates lineages infecting Strigiformes.
Text-fig. 1. D&E tree of Endress and Doyle (2009), from the combined morphological and molecular analysis of Doyle and Endress (2000), with modifications based on more recent data, showing the inferred evolution of the reticulum grading character (39). Boxes under names of taxa indicate their character state; shading of branches indicates their reconstructed state based on parsimony optimization with MacClade (Maddison and Maddison 2003). Nymph = Nymphaeales, Aust = Austrobaileyales, Chlor = Chloranthaceae, Piper = Piperales, Ca = Canellales, Magnol = Magnoliales. in Early Cretaceous Monocots: A Phylogenetic Evaluation
Text-fig. 1. D&E tree of Endress and Doyle (2009), from the combined morphological and molecular analysis of Doyle and Endress (2000), with modifications based on more recent data, showing the inferred evolution of the reticulum grading character (39). Boxes under names of taxa indicate their character state; shading of branches indicates their reconstructed state based on parsimony optimization with MacClade (Maddison and Maddison 2003). Nymph = Nymphaeales, Aust = Austrobaileyales, Chlor = Chloranthaceae, Piper = Piperales, Ca = Canellales, Magnol = Magnoliales.
Figure 1. A in New molecular data for parasites Hammerschmidtiella indicus and Thelandros scleratus (Nematoda: Oxyurida) to infer phylogenetic position
Figure 1. A phylogenetic tree based on the 18S rDNA sequences was constructed by using the ME method. The evolutionary distance values are indicated at the nodes. The GenBank accession number for each sequence is given adjacent to the name of the corresponding species.
Fig. 1 in On Trimeresurus Fasciatus (Boulenger, 1896) (Serpentes: Crotalidae), With A Discussion On Its Relationships Based On Morphological And Molecular Data
Fig. 1. Trimeresurus fasciatus. Holotype (BMNH 96.4.29.46). General view. Photograph by Jean-Christophe de Massary.
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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.