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4,722 results for “Morphological Data”
Morphometric data from: Incongruent molecular and morphological variation in the crab spider Synema globosum (Araneae: Thomisidae) in Europe
<p>Here we provide the complete set of files used by <a href="https://doi.org/10.3897/zookeys.1078.64116">Urfer et al. (2021</a>, see References section below for the complete citation of the publication) for the morphometric and the molecular analysis. In particular, we provide the following documents:</p> <p><br> PART 1: MORPHOMETRIC ANALYSIS</p> <p>- 1_Synema_data_multiple_imputation_mice.R: R-script used for replacing NAs.</p> <p>- 1_Synema_data_NA_imputed.csv: Dataset with raw values (in millimeters) of all 28 specimens used for the morphometric analysis. Each specimen was measured 4 times. NAs replaced using the R-script "Synema_multiple_imputation_mice.R" above. This is the datafile used for all morphometric analyses.</p> <p>- 1_Synema_data_with_NA.csv: Dataset with raw values (in millimeters) of all 28 specimens. Each specimen was measured 4 times. NAs not replaced.<br> <br> - 1_Synema_Reliability.R: R-script for calculating reliability.<br> <br> - 1_Synema_Reliability_supplementary_figure.pdf: Results of reliability analysis presented in a bar plot.</p> <p>- 1_Synema_Reliability_supplementary_table.txt: Results of reliability analysis presented in a table.<br> <br> - 1_Synema_Shape_PCA_and_PCA_Ratio_Spectrum.R: R-script for calculating the shape PCA and the PCA Ratio Spectrum of the first shape PC. You may get the necessary MRA source script from http://doi.org/10.5281/zenodo.4250142<br> <br> - Synema_globosum_AR9379_PV.jpg, Synema_globosum_AR9379_PV.jpg, Synema_globosum_AR9379_PV.jpg, etc.: Photographs taken with a LEICA M205 C stere-omicroscope.</p> <p> 1. Numbers after AR_ refer to the inventory number of the specimens in the Natural History Musuem Bern (NMBE). The specimen number was also used in the data file.<br> 2. The photo named "Synema_globosum_AR9163_with_measurements" shows the position of the measurements. Otherwise, the measurements are not indicated in the raw photos.</p> <p><br> Example image Character name Definition<br> Synema_globosum_AR9163_with_measurements cym.l Cymbium lenght Distance of the anterior margin to the tip of the cymbium<br> Synema_globosum_AR9163_with_measurements cym.b Cymbium breadth widest breadth of the cymbium<br> Synema_globosum_AR9163_with_measurements bul.b Bulb breadth widest breadth of the genital bulbus<br> Synema_globosum_AR9163_with_measurements tib.b Tibia breadth breadth of the tibia base at the patella joint</p>
Experimental data for 'Scaling laws for coastal overwash morphology'
<p>This dataset contains the experimental data described in Lazarus, ED (2016) Scaling laws for coastal overwash morphology, <em>Geophysical Research Letters</em>, 43, 12113–12119, <a href="https://doi.org/10.1002/2016GL071213">https://doi.org/10.1002/2016GL071213</a>.</p> <p>The physical experiments that produced these data were conducted at St Anthony Falls Laboratory (University of Minnesota, USA) in December 2014. The experiments were conducted in a 3 x 5 x 0.6 m tank filled with well-sorted coarse river sand. The tank and the experimental trials are detailed in Text S1 of the Supporting Information for Lazarus (2016): <a href="https://agupubs.onlinelibrary.wiley.com/action/downloadSupplement?doi=10.1002%2F2016GL071213&file=grl55284-sup-0001-SI.pdf">https://agupubs.onlinelibrary.wiley.com/action/downloadSupplement?doi=10.1002%2F2016GL071213&file=grl55284-sup-0001-SI.pdf</a></p> <p>This dataset consists of two *.csv files:</p> <ul> <li>'...THROATS.csv' – morphometric data for <strong>erosional</strong> (throat) features in the experimental barrier</li> <li>'...WASHOVER.csv' – morphometric data for <strong>depositional</strong> (washover) features on the back-barrier floodplain</li> </ul> <p>Both files have the same general column headings: feature width (in the alongshore dimension) [m], feature length (in the cross-shore dimension) [m], feature area [m<sup>2</sup>], feature volume [m<sup>3</sup>], alongshore spacing (centroid-to-centroid distance to neighbouring feature) [m], and real alongshore position [m].</p> <p>All features were formed along an initially geometrically uniform (topographically homogenous) trapezoidal barrier under inundation-type forcing (denoted in 'forcing' column). These data report the compiled results of three experimental trials (denoted in 'trial' column).</p> <p>Note that these data are also available as part of the Supporting Information for Lazarus (2016), but the format in which they were originally uploaded is not conducive to straightforward integration into open-source analysis. Publishing them here, in this tidier format, is an effort to rectify that.</p>
Data, scripts, and R Notebook for Carneiro et al 2023. Flight performance and wing morphology in the bat Carollia perspicillata: biophysical models and energetics. Integrative Zoology DOI:10.1111/1749-4877.12707
<p>Files provided as supporting information for the paper by Carneiro et al. 2023. Flight performance and wing morphology in the bat <em>Carollia perspicillata</em>: biophysical models and energetics. Integrative Zoology. DOI:10.1111/1749-4877.12707</p> <p>File descriptions</p> <p>ArmTA.txt - Temperature and surface areas for arms of <em>C. perspicillata</em> after flight experiment<br> BodyTA.txt - Temperature and surface areas for body of <em>C. perspicillata</em> after flight experiment<br> HeadTA.txt - Temperature and surface areas for head of <em>C. perspicillata</em> after flight experiment<br> WingTA.txt - Temperature and surface areas for wings (patagium) of <em>C. perspicillata</em> after flight experiment<br> WingMorph.txt - Morphological variables measured in the body and wings of <em>C. perspicillata</em><br> HeatLoss.R - Function to estimate heat loss (Qt)<br> PowFlight.R - Function to estimate minimum power required to fly<br> Script-HeatLoss-FlightPerformance.R - R script with set of analyses performed<br> SupportingInformationFile.docx - R notebook with set of analyses performed, word format<br> SupportingInformationFile.nb.html - R notebook with set of analyses performed, html format<br> SupportingInformationFile.Rmd - R notebook with set of analyses performed (R markdown)</p> <p>For the R scripts (Script-HeatLoss-FlightPerformance.R) and notebook (<br> SupportingInformationFile.Rmd) to work and be compiled, all files need to be copied to the same folder.</p>
Data set: Morphological evolution and niche conservatism across a continental radiation of Australian blindsnakes
<h1>Repository for "Morphological evolution and niche conservatism across a continental radiation of Australian blindsnakes"</h1> <p>---</p> <p>These data scripts were used to perform analyses included in the research paper "Morphological evolution and niche conservatism across a continental radiation of Australian blindsnakes" </p> <p>Main questions for the study:</p> <p>1. What are the main axes of morphological variation?<br>2. Does variation in morphology among species correlate with their current environments? <br>3. Are lineages that occupy ecologically similar habitats morphologically convergent? <br>4. Is speciation predominantly allopatric or sympatric? <br>5. Do sister species have greater morphological and ecological niche overlap than expected relative to non-sister species pairs?</p> <h2>## Data structure</h2> <p>Contents in the data folder is archived as a zip and can be downloaded from Zenodo (for all versions see https://zenodo.org/doi/10.5281/zenodo.10397830). Once you unzip the zipped files, you will see three folders and some files that are no in any folders. </p> <p>/data/ - files that were manually created and the phylogeny</p> <p>/data/script_generated_data/ - A combination of processed data needed to run the analyses </p> <p>/data/dorsal/ - photographs of the head from the dorsal view. These photos were used for digitising landmarks and semilandmarks. </p> <p>/data/worldclim2_30s/ - cropped and merged annual temperature from WorldClim2 (Fick and Hijmans 2017), soil bulk density from <a href="https://esoil.io/TERNLandscapes/Public/Pages/SLGA/GetData.html">Soil and Landscape Grid of Australia</a>, and Global Aridity Index from Zomer et al. (2022). <br><br>/DREaD/ - contains some files required to replicate DREaD analysis</p> <h2>## Code/Software</h2> <p>All scripts can be run using open source software. Scripts should be run in order to create necessary files that will be saved in /data/script_generated_data/ for further scripts. R is required to run R scripts (.R).</p> <h3>### /Code</h3> <p> - utility/*.R - scripts for custom functions. These are sourced in other scripts.<br> - DREaD/*.R - scripts associated with DREaD analyses<br> - 00_linear_measurement_shaperatio.R - script used to account for sexual dimorphism and calculate conventional PCA. Addresses Q1.<br> - 01_model_fitting.R - script used to address Q2 and plot visualisations.<br> - 02_convergence.R - this script calculates Ct1-4 and C5 scores. Addresses Q3.<br> - 02_convergence_model_fitting.R - this script evaluates fit of different evolutionary models to traits. Addresses Q3.<br> - 02_convergence_test_simulations.R - simulation studies to show that our phylogeny has sufficient power to detect convergence.<br> - 03_niche_enmtools_bias_account.R - calculates ecological niche models (ENMs) for each species using MAXENT. Runs Age-Overlap Correlation tests for geography and ENMs. Partially addresses Q4.<br> - 03_DREaD_Blindsnakes_AS.R - script to run DREaD analysis. <br> - 03_morpho_niche_overlap_plots.R - Runs Age-Overlap Correlation tests for body shape and snout shape. Plots AOCs. Partially addresses Q4. <br> - 04_pairwise_distance_test.R - Binomial tests between sister and non-sister pairs for ENMs and Geographic Range. Partially addresses Q5<br> - 04_morpho_pairwise.R - Binomial tests between sister and non-sister pairs for body shape and snout shape. Partially addresses Q5</p> <h2>## Contact</h2> <p>Should you have questions about these scripts or would like to request raw data, please do not hesitate to contact Sarin Tiatragul (contact information can be found in the paper) or on Github (https://github.com/stiatragul/blindsnakemorphoevo)</p> <h2>## References</h2> <p><a name="ref-fickWorldClim2017"></a>Fick, S. E., and R. J. Hijmans. 2017. <a href="https://doi.org/10.1002/joc.5086">WorldClim 2: New 1-km spatial resolution climate surfaces for global land areas</a>. International Journal of Climatology 37:4302–4315.</p> <p><a name="ref-zomerVersion2022"></a>Zomer, R. J., J. Xu, and A. Trabucco. 2022. <a href="https://doi.org/10.1038/s41597-022-01493-1">Version 3 of the global aridity index and potential evapotranspiration database</a>. Scientific Data 9:409.</p>
Merging Bioactivity Predictions from Cell Morphology and Chemical Fingerprint Models Using Similarity to Training Data
<p>The applicability domain of machine learning models trained on structural fingerprints for the prediction of biological endpoints is often limited by the lack of diversity of chemical space of the training data. In this work, we developed “similarity-based merger models” which combined the output of individual models trained on cell morphology (based on Cell Painting) and chemical structure (based on chemical fingerprints) and the structural and morphological similarities of the test compounds to training compounds. We applied these similarity-based merger models using logistic equations to weigh individual features and predicted assay hit calls of 177 assays from ChEMBL, PubChem and the Broad Institute, where the required Cell Painting annotations were available. We found that the similarity-based merger models outperformed other models with an additional 20% assays (79 out of 177 assays) with an AUC>0.70 compared with 65 out of 177 assays using structural models and 50 out of 177 assays using Cell Painting models. Our results demonstrate that similarity-based merger models combining structure and cell morphology models can more accurately predict a wide range of biological assay outcomes and expand the applicability domain by better extrapolating to new structural and morphology spaces.</p>
Supplementary data: Agro-morphological and molecular characterization reveal deep insights in promising genetic diversity and marker-trait associations in Fagopyrum esculentum and F. tataricum
<p>Our study focuses on the global/European buckwheat germplasm collected as part of the ECOBREDD project. The potential of this highly diverse collection for organic buckwheat breeding was evaluated at two complementary levels: phenotypic and genetic. Here, we characterized the phenotypic and genetic diversity of a global collection of the two cultivated buckwheat species <em>Fagopyrum esculentum</em> and <em>F. tataricum</em> (190 and 51 accessions, respectively) using 37 agro-morphological traits and 24 SSR markers (Simple Sequence Repeats) (see publication and info sheet of the data).</p>
Supplementary data for "The subgenual organ complex in stick insects: Functional morphology and mechanical coupling of a complex mechanosensory organ"
<p>µCT-scans of the upper tibial regions of the foreleg (T1) and the midleg (T2) of <em>Ramulus artemis</em> (Westwood, 1859), <em>Carausius morosus</em> (Sinéty, 1901), and <em>Sipyloidea sipylus</em> (Westwood, 1859). For use of scans, please cite the following publication:</p> <p>Strauß, J., Moritz, L. & Rühr, P.T. (<strong>2021</strong>): The subgenual organ complex in stick insects: Functional morphology and mechanical coupling of a complex mechanosensory organ. <em>Frontiers in Ecology and Evolution (Research Topic “Evolutionary Biomechanics of Sound Production and Reception”)</em>. doi: <a href="https://doi.org/10.3389/fevo.2021.632493">10.3389/fevo.2021.632493</a>.</p> <p>All scans were performed with a commercial μCT desktop system (Skyscan 1272, Bruker microCT, Kontich, Belgium) at the Zoological Research Museum Alexander Koenig, Leibniz Institute for Animal Biodiversity, Bonn, Germany.</p> <p><strong>µCT scan settings of all samples:</strong></p> <p><em>Ramulus artemis:</em></p> <ul> <li>tube voltage = 30 kV</li> <li>ube current = 200 μA</li> <li>target = tungsten</li> <li>no filter</li> <li>total sample rotation = 360°</li> <li>angular step size = 0.2°</li> <li>exposure time = 1980 ms</li> <li>binning = 1x1</li> <li>averaging = 8</li> <li>random movement = 15 px</li> <li>voxel size = 1.8 μm</li> <li>fixation: Bouin's solution (24 hours)</li> <li>staining: 0.3% PTA (21 days)</li> <li>storage: 70% EtOH</li> <li>surrounding medium in scan: 70% EtOH</li> <li>filenames: Ramulus_artemis_T1.tif; Ramulus_artemis_T2.tif</li> </ul> <p><em>Carausius morosus:</em></p> <ul> <li>tube voltage = 29 kV</li> <li>ube current = 200 μA</li> <li>target = tungsten</li> <li>no filter</li> <li>total sample rotation = 360°</li> <li>angular step size = 0.2°</li> <li>exposure time = 1900 ms</li> <li>binning = 1x1</li> <li>averaging = 5</li> <li>random movement = 15 px</li> <li>voxel size = 1.0 μm</li> <li>fixation: Bouin's solution (24 hours)</li> <li>staining: 0.3% PTA (21 days)</li> <li>storage: 70% EtOH</li> <li>surrounding medium in scan: 70% EtOH</li> <li>filenames: Carausius_morosus_T1.tif; Carausius_morosus_T2.tif</li> </ul> <p><em>Sipyloidea sipylus:</em></p> <ul> <li>tube voltage = 29 kV</li> <li>ube current = 200 μA</li> <li>target = tungsten</li> <li>no filter</li> <li>total sample rotation = 360°</li> <li>angular step size = 0.2°</li> <li>exposure time = 1900 ms</li> <li>binning = 1x1</li> <li>averaging = 7</li> <li>random movement = 15 px</li> <li>voxel size = 1.8 μm</li> <li>fixation: Bouin's solution (24 hours)</li> <li>staining: 0.3% PTA (21 days)</li> <li>storage: 70% EtOH</li> <li>surrounding medium in scan: 70% EtOH</li> <li>filenames: Sipyloidea_sipylus_T1.tif; Sipyloidea_sipylus_T2.tif</li> </ul>
Supporting Data - Taxonomic reassessment of Tetrapygus niger (Arbacioida, Echinoidea): molecular and morphological evidence support its placement in Arbacia
<p>This dataset contains the accession numbers and links of the sequences of the specimens analyzed by this work, other sequences used for the analyses can be found in the original article. The species from which the sequences were extracted are: Tetrapygus niger Molina, 1782; Arbacia dufresnii Blainville, 1825; Arbacia spatuligera Valenciennes, 1846 and Coelopleurus floridanus A. Agassiz, 1872. The accession numbers for the Cytochrome Oxidase subunit I (COI) and 28S of the nuclear genome are presented separately.</p><p>In addition, the morphological data of Tetrapygus niger (Test diameter, test height and peristome diameter) presented in this study are shown, as well as their collectors, corresponding collection, country and locality.</p>
Data set for "Axonal and dendritic morphology of excitatory neurons in layer 2/3 mouse barrel cortex imaged through whole-brain two-photon tomography and registered to a digital brain atlas"
<p>Data set for: Liu Y, Foustoukos G, Crochet S and Petersen CCH (2022) Axonal and dendritic morphology of excitatory neurons in layer 2/3 mouse barrel cortex imaged through whole-brain two-photon tomography and registered to a digital brain atlas. Front Neuroanat 15: 791015. https://doi.org/10.3389/fnana.2021.791015</p> <p>There are 2 files in this upload:</p> <p>1. The file named "<strong>2022_Liu_FrontNeuroanat.pdf</strong>" is the Open Access pdf of the online publication in Frontiers in Neuroanatomy.</p> <p>2. The file named "<strong>Liu_data_code.zip</strong>" (~1 GB) is a zipped version of a folder ‘<em>Liu_data_code</em>’, which contains the data analyzed in the study along with the Python codes used to generate the published figures. The original high resolution image stacks obtained through whole-brain two-photon serial tomography are unfortunately too large for Zenodo, and only highly-downsampled data are included in this upload, which were used for registration with the Allen CCFv3. Instructions on how to view and analyse the anatomical data are provided in the 'README.docx' file, which you will find upon unzipping the folder.</p> <p> </p>
Dataset In-vivo estimation of axonal morphology from MRI and EEG data
<p>This dataset includes the data underlying the conclusions made in the scientific article:<br> "In-vivo estimation of axonal morphology from MRI and EEG data"<br> Rita Oliveira, Andria Pelentritou, Giulia Di Domenicantonio, Marzia De Lucia, Antoine Lutti</p> <p><a href="https://www.frontiersin.org/articles/10.3389/fnins.2022.874023/full">https://www.frontiersin.org/articles/10.3389/fnins.2022.874023</a></p> <p>The main objective is to use data collected in-vivo in humans to estimate microscopic morphologic features of the white matter tracts.</p> <p>The in-vivo data estimated along a white matter tract of interest includes:<br> • the MRI g-ratio sampled along the visual transcallosal white matter tract<br> • a measure of conduction velocity estimated from an EEG measure of interhemispheric transfer time (IHTT)</p> <p>The microscopic morphologic features of white matter we estimate are:<br> • the axonal radius distribution, P(r)<br> • the g-ratio dependence on the radius, g(r)</p> <p>-------------------------------------------------------------------------<br> CONTENT:</p> <p>This package includes data for all the 14 subjects used in the corresponding scientific article:<br> • G-ratio values sampled along the transcallosal visual tract <br> double vector (# MRI_gratio samples x 1): G_ratio_samples.mat<br> • Length of the transcallosal visual tract <br> double: Tract_length.mat<br> • Current source densities (pA.m) of each trial, brain vertice and time <br> point for the left brain visual cortex <br> double 3 matrix (#trials x #vertices x #timepoints): Source_reconstruction_left_brain_V1V2.mat <br> • Current source densities (pA.m) of each trial, brain vertice and time <br> point for the right brain visual cortex <br> double 3 matrix (#trials x #vertices x #timepoints): Source_reconstruction_right_brain_V1V2.mat <br> • Vector of the time sample of the EEG epochs<br> double vector (1 x #time points): time_vec.mat</p> <p>The codes used in the analysis of this data are available on our online repository: <a href="https://github.com/LREN-physics/AxonalMorphology">https://github.com/LREN-physics/AxonalMorphology</a>.</p> <p>-------------------------------------------------------------------------<br> AUTHORS:</p> <p>Author: Rita Oliveira<br> PIs: Marzia De Lucia, Antoine Lutti</p> <p>Laboratory for Neuroimaging Research</p> <p>Lausanne University Hospital & University of Lausanne, Lausanne, Switzerland</p> <p>Copyright (C) 2022 Laboratory for Neuroimaging Research</p>
Supplementary Information and Data for "Unveiling the 3D Morphology of Epitaxial GaAs/AlGaAs Quantum Dots"
<p>Raw and processed TEM and AFM data for the article <strong><em>Unveiling the 3D Morphology of Epitaxial GaAs/AlGaAs Quantum Dots</em></strong>.</p> <p>Paper: <a href="https://doi.org/10.1021/acs.nanolett.4c02182" target="_blank" rel="noopener">https://doi.org/10.1021/acs.nanolett.4c02182</a></p> <p>Preprint: <a href="https://arxiv.org/abs/2405.16073" target="_blank" rel="noopener">https://arxiv.org/abs/2405.16073</a></p> <p>The TEM data has a PDF information file included with description of the file types and how to open them.</p> <p>The AFM Nanosurf .nid files can be opened, e.g., with <a href="http://gwyddion.net/" target="_blank" rel="noopener">Gwyddion</a>.</p>
Supporting data and codes for: A new biological species in the Mercurialis annua polyploid complex: functional divergence in inflorescence morphology, hybrid sterility and possible introgression
<p>This GitHub repository includes R codes and datasets for the paper: A new biological species in the Mercurialis annua polyploid complex: functional divergence in inflorescence morphology, hybrid sterility and possible introgression</p>
Supporting data for the manuscript: "The Role of Mesoscale Cloud Morphology in the Shortwave Cloud Feedback"
<p>This repository contains supporting data for the manuscript "The Role of Mesoscale Cloud Morphology in the Shortwave Cloud Feedback" in <em>Geophysical Research Letters</em>. Detailed descriptions of these datasets can be found in the manuscript text as well as in the file descriptions.</p>
Microsatellite genotype data and leaf morphological data of the publication "Bidirectional gene flow between Fagus sylvatica L. and F. orientalis Lipsky despite strong genetic divergence"
<p>These data sets were used for analyses in the publication "Bidirectional gene flow between <em>Fagus sylvatica</em> L. and<em> F. orientalis</em> Lipsky despite strong genetic divergence" accepted in Forest Ecology and Management <a href="https://www.sciencedirect.com/journal/forest-ecology-and-management/vol/537/suppl/C">Volume 537</a>, 1 June 2023, 120947, <a href="https://doi.org/10.1016/j.foreco.2023.120947">https://doi.org/10.1016/j.foreco.2023.120947</a></p> <p>For details about the data, please read the corresponding ReadMe files.</p>
Morphological cladogenesis and terminal dwarfing in extinct Late Miocene through Pliocene menardiform globorotalids: New complementary data to «Evolutionary prospection in the Neogene planktic foraminifer Globorotalia menardii and related forms from ODP Hole 925B (Céara Rise, western tropical Atlantic): evidence for gradual evolution superimposed by long distance dispersal ?, Swiss J. Palaeontology, 135:205-248»
<p>A complementary morphometric data set is provided to the study of Knappertsbusch (2016) about the shell evolution of menardiform globorotalids (Neogene planktic foraminifera) at ODP Hole 925B from Céara Rise in the the western tropical Atlantic. The new measurements confirm splitting of extinct <em>Globorotalia multicamerata</em> from the <em>G. menardii</em> stock via the intermediate form <em>G. limbata</em> between about 6 Ma to 5 Ma ago. After splitting both <em>G. limbata</em> and <em>G. multicamerata</em> show gradual divergence from <em>G. menardii</em> in several shell parameters illustrating morphological cladogenesis. Between 2.88 Ma and 2.59 Ma the same parameters show a concerted trend towards reduced values indicating pre-extinction dwarfing. A comparison with published literature data of Delta<sup>18</sup>O trends between species, that populated the mixed layer (<em>Globigerinoides sacculifer</em>) and the thermocline layer (<em>Neogloboquadrina dutertrei</em>) at this location during those times suggests, that both divergence and subsequent dwarfing trends were probably the results of changes in upper watermass stratification.</p> <p>The complementary data set is provided in six zipped archives APPENDIX A, B, C, D, E and F (zipped with free software 7-Zip 22.00 (x64), 2022-06-15 from 1999-2022 Igor Pawlow), together with a description of the data in file Report_925B_suppl_1.pdf.</p>
Supplementary data for the journal article "Quantifying the impact of 3D pore space morphology on diffusive mass transport in loam and sand"
<p>Binarized cutouts (black=pore, white=soil) of 3D CT images of soil samples from loam and sand together with geometrical descriptors and diffusive properties computed on these cutouts. The geometrical descriptors include, among others, porosity, specific surface area, geodesic tortuosity, geometric tortuosity, constrictivity, mean chord length and mean of spherical contact distribution. Diffusion is quantified by the so-called M-factor which equals the ratio of the effective and intrinsic diffusivity.</p> <p>This data supplements the journal article "Quantifying the impact of 3D pore space morphology on diffusive mass transport in loam and sand". Additional information can be found there.</p>
Geographic range size and species morphology determines the organization of sponge host-guest interaction networks across tropical coral reefs (Raw data)
<p>Datasets for the analysis developed in the Article "<em><strong>Geographic range size and species morphology determines the organization of sponge host-guest interaction networks across tropical coral reefs</strong></em>". For more information, please refer to the original publication.</p> <p>Network_Structural_Index_&_SpogeTraits.csv <- Structural Index for the sponge-dwelling fauna network, sponge accumulated area and sponges’ morphology.</p> <p>NWTA_CoralReefs_Sponges_ interactions.csv <- Relationship between host sponges and guest fauna in the Northwester Atlantic coral reefs</p> <p>NWTA_CoralReefs_Sponge_reacords.csv <- Sponge species incidence records in the Northwester Atlantic coral reefs</p> <p>sponges_morphological_description.csv <- Sponge morphological standardization</p> <p>Network.html <- Interactive sponge-dwelling fauna network</p> <p>Enjoy!<br> </p>
Supplementary data for the article "Head and dependent marking and dependency length in possessive noun phrases: a typological study of morphological and syntactic complexity"
<p>This material contains the Supplementary material (including the R-scripts) of the following article. Please cite the article when using the data.</p> <p>Sinnemäki, Kaius and Haakana, Viljami. 2023. Head and dependent marking and dependency length in possessive noun phrases: a typological study of morphological and syntactic complexity. <em>Linguistics Vanguard</em> 9(s1). 45-57. <a href="https://doi.org/10.1515/lingvan-2021-0074">https://doi.org/10.1515/lingvan-2021-0074</a></p>
Stachewicz et al. 2021: Trait correlation, phylogenetic signal in Carabidae morphology (repackaging of occurrences published by the NEON Biorepository Data Portal)
Stachewicz JD, Fountain-Jones NM, Koontz A, Woolf H, Pearse WD, Gallinat AS. 2021. Strong trait correlation and phylogenetic signal in North American ground beetle (Carabidae) morphology bioRxiv 02.12.431029; doi: https://doi.org/10.1101/2021.02.12.431029 Many NEON samples and specimens used in this work resulted from NEON prototype data and will not be archived in the Biorepository. See the appendices in the above linked article for a full list of NEON samples and specimens and their associated collection data. Additionally, see appendices of above linked article for specimen-level morphological trait measurements and genetic sequence data.
Fig. 3 in A new western Atlantic snapping shrimp of the Alpheus macrocheles group (Caridea, Alpheidae) revealed by morphological, molecular and color data
Fig. 3. Alpheus ramosportoae sp. nov., paratype, ♂, from seamounts of the North Chain, Ceará, northeastern Brazil (MOUFPE 13703). A. Second pereiopod, lateral view. B. Third pereiopod, lateral view. C. Fourth pereiopod, lateral view. D. Fifth pereiopod, lateral view. E–G. Third to fifth pereiopods, detail of propodus, lateral view. H–I. Third and fourth pereiopods, detail of dactylus. Scale bars: A–G = 0.5 mm; H–I = 0.25 mm.
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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.