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Supplementary material 2 from: Guzow-Krzemińska B, Sérusiaux E, van den Boom PPG, Brand AM, Launis A, Łubek A, Kukwa M (2019) Understanding the evolution of phenotypical characters in the Micarea prasina group (Pilocarpaceae) and descriptions of six new species within the group. MycoKeys 57: 1-30. https://doi.org/10.3897/mycokeys.57.33267
: Data type: PDF file
Supplementary material 1 from: Guzow-Krzemińska B, Sérusiaux E, van den Boom PPG, Brand AM, Launis A, Łubek A, Kukwa M (2019) Understanding the evolution of phenotypical characters in the Micarea prasina group (Pilocarpaceae) and descriptions of six new species within the group. MycoKeys 57: 1-30. https://doi.org/10.3897/mycokeys.57.33267
: Data type: PDF file
Phenotype data Eucalyptus wood properties CNB Cirad-Ufla
<p>Phenotypic data obtained by NIR prediction on wood of the studied trees (5 trees for 10 clones of CENIBRA in 3 sites in Brazil) : wood density, stiffness and microfibril angle of cell walls</p> <p> </p>
Figure 2 from: Guzow-Krzemińska B, Sérusiaux E, van den Boom PPG, Brand AM, Launis A, Łubek A, Kukwa M (2019) Understanding the evolution of phenotypical characters in the Micarea prasina group (Pilocarpaceae) and descriptions of six new species within the group. MycoKeys 57: 1-30. https://doi.org/10.3897/mycokeys.57.33267
Figure 2 Morphology of newly described Micarea species AM.aeruginoprasina (holotype) BM.azorica (holotype) CM.isidioprasina (holotype) DM.microsorediata (holotype) EM.nigra (holotype) FM.pauli (holotype). Scale bars: 200 µm (A−C, E); 300 µm (D, F).
Figure 1 from: Guzow-Krzemińska B, Sérusiaux E, van den Boom PPG, Brand AM, Launis A, Łubek A, Kukwa M (2019) Understanding the evolution of phenotypical characters in the Micarea prasina group (Pilocarpaceae) and descriptions of six new species within the group. MycoKeys 57: 1-30. https://doi.org/10.3897/mycokeys.57.33267
Figure 1 Maximum likelihood tree based on three-loci dataset. Bootstrap supports ≥ 70 for ML and posterior probabilities ≥ 0.95 (second value) for Bayesian methods are indicated near the branches. The highly supported clades with previously described species represented by numerous sequences are collapsed. Herbarium collection numbers for newly sequenced specimens precede the names of species and type specimens are marked. Newly described species are marked in bold. Micareamicrococca (orange) and M.prasina (blue) clades are indicated with shading. Ancestral states for selected characters reconstructed based on binary or multistate datasets using maximum parsimony (MP) or maximum likelihood methods (ML) are marked for the main clades: M.prasina group, M.micrococca clade and M.prasina clade using red (= present/significant) and white (= absent/insignificant) boxes or ? (= uncertain).
Fig. 11 in Tracking the variability of phenotypic traits on a molecular phylogeny: an example from scolopendrid centipedes in peninsular India
Fig. 11 Number of VL spines on the ultimate leg prefemur mapped onto phylogeny of Indian Digitipes
Fig. 10 in Tracking the variability of phenotypic traits on a molecular phylogeny: an example from scolopendrid centipedes in peninsular India
Fig. 10 Number of VM spines on the ultimate leg prefemur mapped onto phylogeny of Indian Digitipes
Fig. 4 in Tracking the variability of phenotypic traits on a molecular phylogeny: an example from scolopendrid centipedes in peninsular India
Fig. 4 First tergite with complete paramedian sutures mapped onto phylogeny of Indian Digitipes
Fig. 3 in Variability Of The Phenotypic Composition Of Cepaea Hortensis (Gastropoda, Helicidae) In Western Ukraine: In Space And Time
Fig. 3. Location of all (main and additional) sites in Lviv, where only the variants of shell coloration common for Western Ukraine (A) or any other coloration variants (B) were registered in 2015–2021.
Text-fig. 1. Eospondylus primigenius (STÜRTZ) Bundenbach, Eschenbach-Bocksberg quarry, Lower Devonian, Lower Emsian (Zlichovian), Hunsrück Slate, specimens PWL 1996 57LS (NMM) top image (A) x 1.5, and PWL 1996 66LS (NMM) bottom image (B) x 1.7. Specimen with rays bent into strong curves. Such flexibility and attitudes of rays differentiate the behavioral ecology of Eospondylus from all other Hunsrück Slate ophiuroids. Delicateness of the top specimen and robustness of the bottom specimen is perhaps the combined result of real phenotypic differences, differences of preserved detail, and differences of distortion of the rock. [courtesy of Herbert Lutz and Thomas Engel; photos by Alexander Glass]. in Isolated Ossicles Of The Family Eospondylidae Spencer Wright, 1966, In The Lower Devonian Of Bohemia (Czech Republic) And Correction Of The Systematic Position Of Eospondylid Brittlestars (Echinodermata: Ophiuroidea: Oegophiurida)
Text-fig. 1. Eospondylus primigenius (STÜRTZ) Bundenbach, Eschenbach-Bocksberg quarry, Lower Devonian, Lower Emsian (Zlichovian), Hunsrück Slate, specimens PWL 1996 57LS (NMM) top image (A) x 1.5, and PWL 1996 66LS (NMM) bottom image (B) x 1.7. Specimen with rays bent into strong curves. Such flexibility and attitudes of rays differentiate the behavioral ecology of Eospondylus from all other Hunsrück Slate ophiuroids. Delicateness of the top specimen and robustness of the bottom specimen is perhaps the combined result of real phenotypic differences, differences of preserved detail, and differences of distortion of the rock. [courtesy of Herbert Lutz and Thomas Engel; photos by Alexander Glass].
Quantitative phenotyping of plant roots using spectral electrical impedance tomography: a rhizotron study on maize and bean crops with optimized measurement design
<div> <h1>Data repository</h1> <br> <div>In this repository, the data accompanying the publication "Quantitative phenotyping of plant roots using spectral electrical impedance tomography: a rhizotron study on maize and bean crops with optimized measurement design", published in "Plant Methods", is stored.</div> <div> </div> <div>The publication can be found at https://doi.org/10.1186/s13007-024-01247-7</div> <br> <h2>Dataset structure</h2> <br> <div>The dataset is structured in the following directories:</div> <br> <h3>complex resistivity inversions</h3> <br> <div>The folder "new_filter_approach_v4_allfreqs", contains all inversion results for frequencies from 0.79 Hz to 1 kHz, sorted by plant name. The data are given as tomodirs (see https://github.com/geophysics-ubonn/crtomo_tools for importing tomodir data within a python framework).</div> <br> <div>In the folder "scatterdata_from_invs", electrical parameters from the inversions are given for x-y-locations in the grid.</div> <br> <h3>dd_fit_results_all_cells</h3> <br> <div>In this folder, the results of the Debye-Decomposition for all cells in the grid are given, together with the x-y-locations in the grid.</div> <br> <h3>dd_fit_results_only_plants</h3> <br> <div>In this folder, the results of the Debye-Decomposition for all cells within the root zone in the grid are given, together with the x-y-locations in the grid.</div> <br> <h3>grid</h3> <br> <div>Contains all files to construct the inversion grid using crtomo_tools.</div> <div> </div> <br> <h3>images_plants</h3> </div> <div> <div> </div> <div>Contains photos for all measured plants, labeled according to the datasets in the manuscript.</div> <br> <div> <h3>impedance_data</h3> </div> <br> <div>In the folder "uncorrected", the raw impedance measurements for all plants are saved (only the correction for the resistivity magnitude is applied to account for the mismatch of 2D inversion and 3D measurement). The folder "corrected" containst the imepdance data that was corrected with background water measurements. The file "md_data_impedance.csv" contains the contact resistances and leakage currents for all measurements.</div> <br> <h3>optimization</h3> <br> <div>This folder contains the results for the synthetic modelling using an optimized (OPT_full) and reduced (OPT_middle) scheme, as described in the manuscript. As for the experimental results, inversions are given in tomodir format. The file "exp.csv" contains the xy-coordinates of the outline of the synthetic polarization signature.</div> <br> <h3>plots</h3> <br> <div>Contains all plots that are shown in the manuscript.</div> <br> <h3>root_data</h3> <br> <div>In the folder "root_area_polygons", the xy-coordinates of the outline of each root system in the rhizotron experiments, extracted from images of the front of the rhizotron, are saved. The file "extracted_elec_params_from_area_v4.csv" contains electical parameters from the inversion results for a number of frequencies for all cells that lie within the root area polygons. The file "Root_traits_final.csv" contains the individually measured root traits via weighing and scanning.</div> <br> <h3>scripts</h3> <br> <div>The scripts "0_plot_methods.py", "1_plot_results.py", "2_plot_discussion.py" and "3_plot_supplementary.py" create all plots shown in the manuscript and save them in the "plots"-directory.</div> </div> <p> </p> <p> </p>
Effects of blood cell traits on cardiovascular morpho-functional phenotypes: Evidence from Mendelian randomization analysis
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PHARAOH: A Collaborative Crowdsourcing Platform for PHenotyping And Regional Analysis Of Histology: KIRK Validation Cohort Grades 3 and 4
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PHARAOH: A Collaborative Crowdsourcing Platform for PHenotyping And Regional Analysis Of Histology: KIRK Validation Cohort Grades 1 and 2
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PHARAOH: A Collaborative Crowdsourcing Platform for PHenotyping And Regional Analysis Of Histology: CCRCC Validation Cohort Grades 3 and 4
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PHARAOH: A Collaborative Crowdsourcing Platform for PHenotyping And Regional Analysis Of Histology: CCRCC Validation Cohort Grades 1 and 2
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Phenotypes of painful TMD in discordant monozygotic twins according to a cognitive-behavioral-emotional model: a case-control study
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Characterization of Rapseed (Brassica napus) Genotypes on the basis of Phenotypic Traits
<p>Characterization of Rapseed (Brassica napus) Genotypes on the basis of Phenotypic Traits </p>
Phenotypic Consequences of Logarithmic Signaling in MAPK Stress Response
<p>How cells respond to dynamic environmental changes is crucial for understanding fundamental biological processes and cell physiology. In this study, we developed an experimental and quantitative analytical framework to explore how dynamic stress gradients that change over time regulate cellular volume, signaling activation, and growth phenotypes. Our findings reveal that gradual stress conditions substantially enhance cell growth compared to conventional acute stress. This growth advantage correlates with a minimal reduction in cell volume dependent on the dynamic of stress. We explain the growth phenotype with our finding of a logarithmic signal transduction mechanism in the yeast Mitogen-Activated Protein Kinase (MAPK) osmotic stress response pathway. These insights into the interplay between gradual environments, cell volume change, dynamic cell signaling, and growth, advance our understanding of fundamental cellular processes in gradual stress environments.</p>
Phenotypically active ORF and CRISPR consensus profiles
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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.