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1,773 results for “Supplementary data,”
Macroalgal genomics illuminate three paths to multicellularity - Supplementary Data - Tables - Data S4
<p>Macroalgae are multicellular, aquatic autotrophs that play vital roles in global climate maintenance and have diverse applications in biotechnology and eco-engineering, which are directly linked to their multicellularity phenotypes. However, their genomic diversity and the evolutionary mechanisms underlying multicellularity in these organisms remain uncharacterized. Here, we sequenced 112 macroalgal genomes from diverse climates and phyla, identifying key genomic features that distinguish them from their microalgal relatives. We found that macroalgae have expanded gene families related to cellular adhesion, extracellular matrix formation, cytoskeletal organization and signaling pathways. We discovered that many of these genes have viral origins and are lineage-specific or conserved among the three major macroalgal phyla: Rhodophyta (red algae), Chlorophyta (green algae) and Ochrophyta (brown algae). Our work reveals genetic determinants of convergent and divergent evolutionary trajectories that have shaped morphological diversity in macroalgae and provides genome-wide frameworks to understand photosynthetic multicellular evolution in marine environments.</p> <p><strong>Table S1.</strong> Functional annotation and metadata for macroalgal species. This is a multi-sheet Excel workbook containing the PFAM count matrix for decontaminated assemblies and their strain metadata, contamination estimates, assembly metrics including BUSCO and N50 scores, and source data for the ternary analysis. Related to Figs. 2 and 3.</p> <p><br><strong>Table S2.</strong> GO enrichment in macroalgal-specific genes. This is a multi-sheet Excel workbook containing enriched GO terms in macroalgal-specific PFAMs conserved in Rhodophyta, Ochrophyta, and Chlorophyta and response screening results comparing means in PFAM counts between divisions. Related to Fig. 3.</p> <p><br><strong>Table S3. </strong>Comparative genomics of micro- and macroalgae. This is a multi-sheet Excel workbook containing response screening tables comparing PFAM and GO variation in micro- compared to macroalgae. Related to Fig. 4.</p> <p><br><strong>Table S4.</strong> Unraveling the macroalgal adhesome. This is a multi-sheet Excel workbook containing macroalgal adhesome atlas and response screens among macroalgal phyla and between micro- and macroalgae. Related to Fig. 4.</p> <p><br><strong>Table S5. </strong>Endogenous viral elements in macroalgae. This is a multi-sheet Excel workbook containing VFAM count matrix and response screening results for comparisons of macroalgal VFAM counts by climate and habitat. This table also includes the EVOP matrix and response screening results comparing EVOPs found in the macroalgal genomes among climates and macroalgal tORFs with EsV-1-7 domains and their codomains. Related to Fig. 5.</p> <p> </p>
Supplementary data and Matlab code for China's HWP carbon balance assessment using Trade-Linked Approach
<p>The supplemtary data describe the fractions of the HWPs disposed of by each option in major countries/regions worldwide.</p> <p>The Matlab code is developed to produce the results of China's HWP carbon balance assessment using Trade-Linked Approach, an innovative generalizable approach for HWP carbon assessment.</p> <p>The data and code are free for academic use only.</p>
A data science approach to climate change risk assessment applied to pluvial flood occurrences for the United States and Canada (Supplementary Material)
<p>This resource is tied to manuscript "A data science approach to climate change risk assessment applied to pluvial flood occurrences for the United States and Canada".</p> <p>It contains: (1) a PDF with additional details on the implementation of GLM, GAM and RF, summarized outputs for two models, a bias analysis of the CRCM and extensive tables from Section 5.2; (2) full outputs for two models; (3) high-resolution figures, and; (4) rasters for selected figures.</p> <p>**</p> <p>Version 2 adds a log-log version of Figure 9 and changes the main PDF file to remove blue section titles.</p>
Advancing the HEIMDALL model: seasonal spectral irradiance through the Pan-Arctic icescape. - Supplementary Data
<p>Code to replicate figures in publication Advancing the HEIMDALL model: seasonal spectral irradiance through the Pan-Arctic icescape.</p>
Supplementary Data: Experimental investigation of volcaniclastic compaction during burial
<p>Raw data files for the uniaxial compaction experiments and acoustic emissions to accompany the main paper</p>
Supplementary Data to "Rapid rise in atmospheric CO2 marked the end of the Late Palaeozoic Ice Age"
<p>Supplementary Data to Jurikova et al. "Rapid rise in atmospheric CO2 marked the end of the Late Palaeozoic Ice Age".</p>
Supplementary data - Multiomic analysis of human kidney disease identifies a tractable inflammatory and pro-fibrotic tubular cell phenotype
Open the record for dataset details and reuse information.
Supplementary Data: A model-independent analysis of b→sμ+μ− transitions with GAMBIT's FlavBit
<p>Supplementary Data</p> <p> A model-independent analysis of b→sμ+μ− transitions with GAMBIT's FlavBit</p> <p>The files in this record contain supplementary data including the samples and plotting scripts used for the results in Bhom. J et al. " A model-independent analysis of b→sμ+μ− transitions with GAMBIT's FlavBit." Samples have been created using <a href="http://gambit.hepforge.org/">GAMBIT</a> and figures can be reproduced with <a href="http://github.com/patscott/pippi">pippi</a>.</p> <p>This record contains:</p> <ul> <li>2 hdf5 files containing the samples produced for this article.</li> <li>2 pip files to create the figures from the samples, using pippi.</li> </ul> <p> </p>
Supplementary data
<p>Supplementary data</p>
Boland et al supplementary data file 1 - Amiodarone
<p>Supplementary Data File 1 containing differentially regulated genes of control treated or Amiodarone treated zebrafish larvae. </p>
Single-Cell Sequencing Reveals Lineage-Specific Dynamic Genetic Regulation of Gene Expression During Human Cardiomyocyte Differentiation - Supplementary Data
<p>Genotype data for 19 cell lines from the Yoruba HapMap population that were used in this study, and summary statistics from QTL calling (see README.md in summary.zip).</p>
Hölzchen et al. (2022) Supplement B. Supplementary data
<p>This dataset contains Supplement B (supplementary data) for Hölzchen et al. (2022) "Estimating crossing success of human agents across sea straits out of Africa in the Late Pleistocene".</p>
Supplementary data for: "Progenitor properties of type II supernovae: fitting to hydrodynamical models using Markov chain Monte Carlo methods"
<p>This entry contains a grid of bolometric light curve and photospheric velocity models applied to stellar evolution progenitors. A full description of the models can be found in Martinez et al. 2020, A&A, 642, A143.</p>
Supplementary data: "Speed of technological transformations required in Europe to achieve different climate goals"
<p>This repository includes results discussed in the paper "<a href="https://arxiv.org/abs/2109.09563">Speed of technological transformations required in Europe to achieve different climate goals</a>"</p> <p>In the paper, we used the open energy modelling framework <a href="https://pypsa.org/">PyPSA</a>, the model <a href="https://github.com/PyPSA/pypsa-eur-sec">PyPSA-Eur-Sec v0.5.0</a> and the cost and technology assumptions included in the repository <a href="https://github.com/PyPSA/technology-data">technology-data v0.2.0</a></p> <p>The directory 'version-baseline' includes the network objects obtained as an outcome of the optimization for the different years and carbon budgets in the baseline scenario.</p> <p>This dataset is released under the <a href="https://creativecommons.org/licenses/by/4.0/">Creative Commons Attribution 4.0 International Licence</a> (CC BY 4.0).</p>
Germline variants in 5 LCLs, supplementary data
<p>These files are supplementary data for the article Laczik M, Erdős E, Ozgyin L, Hevessy Zs, Csősz É, Kalló G, Nagy T, Barta E, Póliska Sz, Szatmári I and Bálint BL: Extensive proteome and functional genomic profiling of variability between genetically identical human B-lymphoblastoid cells. The files (one in Variant Call Format, the other is the index of the former) are outputs from the GATK germline variant calling pipeline, summarizing all the variants found in five isogenic B-lymphoblastoid cell lines. For further details please see the article.</p>
Supplementary Data File
<p>Supplementary Data File of research article: </p> <p>Immune system-wide Mendelian randomization and triangulation analyses support autoimmunity as a modifiable component in dementia-causing diseases; Joni V. Lindbohm, Nina Mars, Pyry N. Sipilä, Archana Singh-Manoux, Heiko Runz, FinnGen, Gill Livingston, Sudha Seshadri, Ramnik Xavier, Aroon D. Hingorani, Samuli Ripatti, Mika Kivimäki; Nature Aging 2022</p> <p> </p>
Supplementary Online Data for Characterizing the hologenome of L. pustulata and tracing genomic footprints of lichenization
<p>Processed data and scripts, as well as the the figures and tables for <em>Characterizing the hologenome of L. pustulata and tracing genomic footprints of lichenization</em>. The <em>zip</em> file contains three subfolders for <em>Chapter 3</em>, <em>Chapter 4</em>, <em>Chapter 5</em> of <em>Characterizing the hologenome of L. pustulata and tracing genomic footprints of lichenization</em>. Each subfolder comes with its own <em>README.md</em> further describing its contents.</p> <p>Furthermore the read mappings against <em>Lasallia pustulata</em> individually, as well as the ones used for the <em>anvi´o</em> visualization, which include <em>L. pustulata</em>, <em>Trebouxia sp.</em> as well as the 499 bacterial scaffolds are given. The <em>Trinity</em> RNAseq assemblies (guided and unguided) are given too.<br> </p>
Supplementary Data for Paper "Efficient Modeling of Water Adsorption in MOFs Using Interpolated Transition Matrix Monte Carlo"
<p>This dataset contains data needed to reproduce all calculations and plots published in paper "Efficient Modeling of Water Adsorption in MOFs Using Interpolated Transition Matrix Monte Carlo", B. Mazur, L. Firlej, and B. Kuchta, 2024, ACS Appl. Mater. Interfaces, DOI: 10.1021/acsami.4c02616. </p>
Supplementary data
<p>This work provides a comprehensive characterization of porcine myocardial tissue, combining biaxial (Bx), simple triaxial shear (STS) and confined compression (CC) tests to analyze its elastic behavior under cyclic loads. We expanded this study to different zones of the ventricular free wall, providing insights into the local behavior along the longitudinal and radial coordinates. The aging impact was also assessed by comparing two age groups (4 and 8 months). Resulting data showed that the myocardium exhibits a highly nonlinear hyperelastic and incompressible behavior. We observed an anisotropy ratio of 2-2.4 between averaged peak stresses in Bx tests and 1-0.59-0.41 orthotropy ratios for normalised fiber-sheet-normal peak stresses in STS tests. We obtained a highly incompressible response, reaching volumetric pressures of 2-7 MPa for perfused tissue in CC tests, with notable differences when fluid drainage was allowed, suggesting a high permeability. Regional analysis showed reduced stiffness and anisotropy (20-25\%) at the apical region compared to the medial, which we attributed to differences in the fiber field dispersion. Compressibility also increased towards the epicardium and apical regions. Regarding age-related variations, 8-month animals showed stiffer response (at least 30\% increase), particularly in directions where the mechanical stress is absorbed by collagenous fibers (more than 90\%), as supported by a histological analysis. Although compressibility of perfused tissue remained unchanged, permeability significantly reduced in 8-month-old animals. Our findings offer new insights into myocardial properties, emphasizing on local variations, which can help to get a more realistic understanding of cardiac mechanics in this common animal model.</p>
Supplementary Data for article: Robust characterization of forest structure from airborne laser scanning – a systematic assessment and sample workflow for ecologists
<p>This is a collection of scripts and research data to assess the robustness of forest structure characterization from airborne laser scanning (ALS). It replicates the main analysis in the article <em>Robust characterization of forest structure from airborne laser scanning – a systematic assessment and sample workflow for ecologists</em> and accompanies the main research data set (<a href="https://doi.org/10.5281/zenodo.10878070" target="_blank" rel="noopener">https://doi.org/10.5281/zenodo.10878070</a>).</p> <p>In this replication study, we assess the derivation of canopy height models (CHMs) from point cloud data, how sensitive CHM algorithms are to pulse density variation and how uncertainties and biases propagate to commonly used forest structure metrics.</p> <p>The main data source for this study are ALS point clouds from nine U.S. sites, acquired by the National Ecological Observatory Network (NEON, 6 sites, 3 km x 3 km) and by the United States Geological Survey's 3DEP program (3 sites, also 3 km x 3 km). The underlying data can be found here: https://data.neonscience.org/data-products/DP3.30024.001 (NEON) and here: https://apps.nationalmap.gov/lidar-explorer (3DEP)</p> <p>The different data layers are:</p> <p><strong>replicate.US.R</strong> </p> <p> is a single R script that contains all the code necessary to reproduce the analyses, including point cloud manipulations and derivation of CHMs from the raw data as well as the overall robustness analysis. To replicate the processing of the raw point clouds step by step, this script should be located in a folder called "rscripts".</p> <p><strong>pointclouds_original.zip</strong></p> <p> is the set of original point clouds (3 km x 3 km in extent) used for the replication test, separated into 9 subfolders/sites. Can be used to reproduce the original workflow by placing them in a folder called "data/original". The script will then automatically produce derived point clouds at pulse densities of 2 and 16 per squaremetre and process them into digital terrain models (DTMs), digital surface models (DSMs) and CHMs. Note that, for convienence, these derived products are also included in a separate .zip file (cf. below).</p> <p><strong>processed_foranalysis.zip</strong></p> <p> is the set of derived products (DTMs, DSMs, CHMs), separated into 9 subfolders/sites, i.e. the result of processing the original point clouds. To use these layers directly with the provided script, they should be put into a folder called "processed_foranalysis".</p> <p><strong>summaries.zip</strong></p> <p><strong> </strong>is a set of summary statistics (as .csv files) that were used to generate the main analysis tables in the replication study. To use these summary statistics directly with the provided script, they should be put into a folder called "summaries".</p> <p><strong>figures.zip</strong></p> <p> is a set of figures displayed in the Supplementary Material of the paper <em>Robust characterization of forest structure from airborne laser scanning – a systematic assessment and sample workflow for ecologists</em>.</p>
ScienceDex guides
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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.