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761 results for “data journal”
Raw data for journal article: "Intracochlear pressure and temporal bone motion interaction under bone conduction stimulation""
<p>This is a data set containing the raw data for figures 3-6 from the journal article:</p> <p>"Intracochlear pressure and temporal bone motion interaction under bone conduction stimulation"</p> <p>Original article DOI: 10.1016/j.heares.2023.108818</p> <p>Original article link: https://pubmed.ncbi.nlm.nih.gov/37267833/</p> <p> </p> <p>The Fig 4-8 data are contained within MATLAB figure (.fig) files, all saved with MATLAB version R2020a.</p> <p>Fig 9-10 data are 3D velocity data for 3 cadaver heads (CH1-3), each recorded at the left (L) and right (R) side, all within the folder "Velocity data".</p> <p>This data are stored within a folder structure indicating the stimulation condition (defined in the journal article). For example "Velocity data\CH1-L\Stim @ BAHA" contains data for the left side of cadaver head 1 (CH1) with stimulation "Stim @ BAHA", as defined in the journal article above. </p> <p>For each combination of cadaver head and stimulation condition there is a TXT file (comma delimited) for the real and imaginary data at each stimulation frequency, and orthogonal velocity axis (X,Y,Z based on the anatomical coordinate system defined in the journal article) as well as the combined (maximum) velocity vector. The data set also includes a TXT file with the position (in same coordinate system the velocity data) of each measurement point and a list of stimulation frequencies.</p> <p>The data set also includes the geometry of the skull bone surface of each cadaver head (CH) in the form of STL file, all within the folder "Skull surface data".</p>
Supplementary files and data Files for "Discordance between mitochondrial, nuclear, and symbiont genomes in aphid phylogenetics: who is telling the truth?" Zoological journal of the Linnean society, 2024, vol 1, issue 4. https://doi.org/10.1093/zoolinnean/zlae098
<p>This repository comprises</p> <ul> <li>a file with all supplementary Tables (<strong>Supplementary_Tables</strong>). Table S1: Collection details and voucher ID for aphid samples from the CBGP-Inrae collection, data origin is given for other specimens. Table S2: Amplification success of long range DNA fragments from mitochondrial genomes . Table S3: Primers used for fluidigm aplification of nuclear genes and sequencing success. Table S4. Genomic features of newly sequenced Buchnera aphidicola with aphid taxonomic affiliation. Table S5: Summary of models used for each ML analysis and corresponding log-likelihood score of the best tree.Table S6: Output of RERConverge analyses.</li> <li>two Supplementary figures: Figure S1: Workflow of phylogenetic analyses as implemented on each dataset. Figure S2: Plot depicting the genome-wide pattern of molecular evolution (dN/dS) between disymbiotic (n = 15) and monosymbiotic aphid (n = 45) branches across the ML phylogeny (horizontal bars indicate 95% CI of the means). <em>P</em> value was calculated by using Wilcoxon Rank test.</li> <li>a word file (Text S1) with : Details of protocol for obtaining mitochondrial genomes through long-range DNA amplifications and Illumina sequencing, and two-step PCR protocole.</li> <li>an archive (archive1) with the mitochondrial AA and DNA matrices and alternative phylogenetic trees under ML and Bayesian analyses ; </li> </ul> <ul> <li>an archive (archive2) with the nuclear AA and DNA matrices and alternative phylogenetic trees under ML and Bayesian analyses</li> <li>an archive (archive 3) with the twelve new <em>Buchnera</em> genome drafts.</li> <li> an archive (archive4) with the <em>Buchnera</em> AA matrices and alternative topologies </li> </ul> <p> </p>
Data on soil variables (with plot IDs) and grassland species traits used for the analysis of grassland vegetation data by Pillar, V.D. (2024) Trait divergence in plant community assembly is generated by environmental factor interactions. Journal of Vegetation Science, 35, e13259. Available from: https://doi.org/10.1111/jvs.13259
<p>File <a href="../api/records/10983049/draft/files/Plot_IDs_990ua.txt/content" target="_blank" rel="noopener noreferrer">Plot_IDs_990ua.txt</a> contains the IDs of the 1-m2 plots used for the analysis of grassland vegetation data by Pillar, V.D. (2024) Trait divergence in plant community assembly is generated by environmental factor interactions. The plot data are stored in the sPlot database (PPBio South Brazilian Grassland Database).</p> <p>File <a href="../api/records/10983049/draft/files/E_990ua_21SoilVar.txt/content" target="_blank" rel="noopener noreferrer">E_990ua_21SoilVar.txt</a> contains data on soil variables evaluated in the 250 m transects, but here expanded to the 990 1-m2 plots (each transect was sampled using 10 1-m2 pots).</p> <p>File <a href="../api/records/10983049/draft/files/B_769spp_4t.txt/content" target="_blank" rel="noopener noreferrer">B_769spp_4t.txt</a> is the species trait database collected in the framework of several research projects in the Quantitative Ecology Lab (EcoQua) and Grassland Vegetation Studies Lab (LevCamp) of Universidade Federal do Rio Grande do Sul (UFRGS). Data gaps were filled by compiled from the TRY database and data imputation.</p> <p> </p> <p> </p>
Data from the journal article "Individual versus combined effects of warming, elevated CO2 and drought on grassland water uptake and fine root traits"
<p>This data file contains all data used in the aforementioned article (DOI: 10.1111/pce.15274). The data was obtained in a long-term multifactor global-change experiment (‘ClimGrass’) in a managed (three cuts, fertilized) C3 grassland near the central European Alps in Styria, Austria (47°29′44.6″N, 14°5′54.6″E). Grassland plots were exposed to six treatments: (i) ambient conditions (control; n = 8); (ii) drought (n = 4); (iii) warming (n = 3); (iv) elevated CO2 (n = 3), (v) future conditions (warming and elevated CO2; n = 3); and (vi) drought in future conditions (warming, elevated CO2 and drought; n = 4). The experiment was conducted during the growing seasons of 2017, 2019, and 2020. The aim was to determine how warming, elevated CO2 and drought individually and interactively affected root water uptake (RWU, calculated from soil water dynamics) as well as the corresponding mass and key traits (specific root length (SRL); specific root area (SRA); mean diameter) of newly produced fine roots (extracted using ingrowth cores) and biomass allocation (fine-root-to-shoot production ratios; R/S ratios). Treatment effects on RWU were studied across varying conditions of soil water content (SWC) and vapour pressure deficit (VPD), referred to as dryness conditions. Fine root characteristics were compared to the maximum hourly in-situ RWU observed. </p> <p>The following data is contained in this file (processed as described in the journal article and, importantly, in the supplementary information):<br>- data_SWC: SWC and precipitation, used to calculate RWU (resolution: hourly; figures: 1)<br>- data_RWU_daily: RWU for the main rooting horizon, fractions of total RWU across depth (resolution: daily; figures: 1, 2, 3)<br>- data_RWU_hourly: RWU for the main rooting horizon, SWC, VPD (resolution: hourly; figures: 1, 4, 5)<br>- data_FineRoots: Mass, traits (SRL, SRA, diameter) and maximum hourly RWU of newly produced fine roots across depth, R/S ratios (resolution: three samplings per growing season; figures: 6, 7)</p> <p>The metadata.xlsx file summarizes the contents of these datasets, including units and descriptions of the variables.</p> <p>Note below: the name of the project funded by the Austrian Academy of Sciences is ClimGrassHydro.</p>
Data archive for the peer-reviewed journal article "Online measurements during simulated atmospheric aging track the strongly increasing oxidative potential of complex combustion aerosols relative to their primary emissions"
<p>This data archive accompanies the article "Online measurements during simulated atmospheric aging track the strongly increasing oxidative potential of complex combustion aerosols relative to their primary emissions", which was accepted in November 2024 in the peer-reviewed journal Environmental Science and Technology Letters. The data archive contains the processed OP_DTT, PM loading, oxidant level, and elemental ratio measurements presented in this journal article. </p>
Data and scripts for Journal of Geophysical Research – Earth Surface publication: Identification of debris-flow channels using high-resolution topographic data: A case study in the Quebrada del Toro, NW Argentina
<p>This data source contains scripts and data associated with the JGR Earth Surface publication <strong>“Identification of debris-flow channels using high-resolution topographic data: A case study in the Quebrada del Toro, NW Argentina”</strong> by A. Mueting, B. Bookhagen, and M. R. Strecker. The Digital Elevation Model (DEM) of the lower part of the Quebrada del Toro and Río Capilla catchment in the NW Argentinian Andes was generated from SPOT-7 tri-stereo images using Ames Stereo Pipeline. The final dataset has a spatial resolution of 3 m. A full description of the DEM generation process and accuracy assessment can be found in the associated paper. The scripts are also available at https://github.com/UP-RS-ESP/DEM_ConnectedComponents.</p>
Data Supplement for 'Curled Wake Development of a Yawed Wind Turbine at Turbulent and Sheared Inflow' - Wind Energy Science Journal
<p>Data Supplement for 'Curled Wake Development of a Yawed Wind Turbine at Turbulent and Sheared Inflow' - Wind Energy Science Journal</p> <p>This database contains the measurement using a model wind turbine with 0.6m diameter(D) in a wind tunnel. A short-range Lidar WindScanner facilitated mapping the wake with a high spatial and temporal resolution in vertical, cross-stream planes at different downstream locations and in a horizontal plane at hub height.</p> <p>The measurement campaign was conducted in the large wind tunnel at ForWind-University of Oldenburg. The wind tunnel has a test section cross-section with the dimensions of 3m x3m. For this study three movable test section elements of 6m length were attached for a total enclosed length of 18m. The roof of the test section was adjusted to compensate for boundary layer growth to achieve a zero pressure gradient for the target wind speed of the experiments, nominally 7.5m/s, with an empty tunnel with no grid or turbine installed. The three-bladed MoWiTO 0.6 wind turbine model(Schottler et al.(2016)), with a hub height (h) of 0.77m and a diameter of 0.58m was placed at a distance of 2.4D downstream of the test section inlet, where the distance was measured to the centre of the rotor. In addition, the distance between the rotor center and the tower center is 110mm.<br> The flow blockage, based on rotor swept area and tower flow-facing area, was 2.7%. The wind turbine controller is based on the torque of the generator (Petrovi ́c et al. (2018)) leading to a tip speed ratio of 5.7 at the operational point during non-misaligned cases with no grid. More information can be found in the paper.</p> <p>The folder contains 12 unique .mat files each containing a matlab structure. The matlab structure conatins the vertical and horizontal scan for each inflow and operational condition:<br> With the upstream turbine installed:<br> - Yaw0_Uniform_NoGrid<br> - 1D, 2D, 3D, 5D, 13D, 16D, Horizontal<br> - Yaw30_Uniform_NoGrid<br> - 1D, 2D, 3D, 5D, 13D, 16D, Horizontal<br> - Yawneg30_Uniform_NoGrid<br> - 1D, 2D, 3D, 5D, 13D, 16D, Horizontal</p> <p> - Yaw0_Uniform_PassiveGrid<br> - 1D, 2D, 3D, 5D, 7D, 10D, Horizontal<br> - Yaw30_Uniform_PassiveGrid<br> - 1D, 2D, 3D, 5D, 7D, 10D, Horizontal<br> - Yawneg30_Uniform_PassiveGrid<br> - 1D, 2D, 3D, 5D, 7D, 10D, Horizontal </p> <p> - Yaw0_BoundaryLayer_PassiveGrid<br> - 1D, 2D, 3D, 5D, 7D, 10D, Horizontal<br> - Yaw30_BoundaryLayer_PassiveGrid<br> - 1D, 2D, 3D, 5D, 7D, 10D, Horizontal<br> - Yawneg30_BoundaryLayer_PassiveGrid<br> - 1D, 2D, 3D, 5D, 7D, 10D, Horizontal </p> <p>Without the upstream turbine installed:<br> - NoTurbine_Uniform_NoGrid<br> - 1D, 2D, 3D, 5D, 13D, 16D<br> - NoTurbine_Uniform_PassiveGrid<br> - 0D, 1D, 2D, 3D, 5D, 7D, 10D<br> - NoTurbine_BoundaryLayer_PassiveGrid<br> - 0D, 1D, 2D, 3D, 5D, 7D, 10D </p> <p>Within each substructure the following parameters are provided:<br> - v_los [m/s] ----------> Line of sight velocity<br> - sigma [m/s] ----------> Spectrum width<br> - x_Global_frame [m] ---> x-coordinate referenced at the lower grid midpoint<br> - y_Global_frame [m] ---> y-coordinate referenced at the lower grid midpoint<br> - z_Global_frame [m] ---> z-coordinate referenced at the lower grid midpoint<br> - xx [m] ---------------> Grid of the x-coordinate referenced at the lower grid midpoint<br> - yy [m] ---------------> Grid of the y-coordinate referenced at the lower grid midpoint<br> - zz [m] ---------------> Grid of the z-coordinate referenced at the lower grid midpoint<br> - uu [m/s] -------------> Horizontal wind speed at the position of the gridded coordinates, these data have been interpolated onto the grid<br> </p> <p>When using this database please reference to the journal paper.</p> <p>All data has been included without warranty, express or implied.</p> <p>For further questions, please contact the corresponding author.<br> </p>
Submission and acceptance data for journals involved in the Taylor & Francis FAIR data pilot
<p>Submission, acceptance and peer review data for journals involved in the Taylor & Francis FAIR data pilot. Data is anonymised. Includes journal article submissions, acceptances and peer review for the years 2018, 2019 and 2020.</p>
Fig. 3 in European Journal of Taxonomy: a deeper look into a decade of data
Fig. 3. Capacity production of European Journal of Taxonomy.
letter to the New England Journal of Medicine: COVID-19 mortality data perplexity
<p>Una explicación para todos los públicos:</p> <p>Lo que he hecho es ver los muertos por COVID-19 declarados por los organismos gubernamentales antes y después de que comience la intervención farmacológica con los productos que se han dado en llamar vacunas por los medios de comunicación y los gobiernos. Primero he considerado el periodo completo de 2020 hasta la "vacunación" y el periodo desde el comienzo de la vacunación hasta el final de los datos (7 de enero 2022). El comienzo es un poco distinto para cada país. Reino Unido y USA comenzaron a principios de diciembre 2020 con gran aparato mediático. Otros no empezaron hasta marzo 2021. Para cada país he calculado el incremento relativo de mortalidad.</p> <p>El resultado es que una gran mayoría tiene incremento positivo: más muertos COVID-19 durante la intervención farmacéutica que antes (2020). En particular USA tiene un incremento considerable. Un test estadístico estándar confirma que la diferencia es significativa, o sea que no podemos afirmar que "no hay diferencia en la mortalidad COVID-19 antes y después del comienzo de la intervención farmacéutica". Por otro lado podemos decir que hay "razones de sobra" para afirmar que hay más muertos COVID-19 durante la "vacunación" que antes de que se comenzara a inocular a las personas.</p> <p>La revista ha comprobado los cálculos y no dicen en su respuesta que sean incorrectos. Ergo, no han falsificado lo que digo en la letter. </p> <p>En segundo lugar he considerado la pregunta ¿hay algún periodo de tiempo en el que la "vacunación" ha conseguido una disminución efectiva de la mortalidad COVID-19?</p> <p>Pudiera ser que al principio de la operación de intervención farmacéutica durante unos días se apreciara un efecto importante de la "vacunación" en forma de descenso de la mortalidad COVID-19, coincidiendo con la afirmación de las empresas de que los anticuerpos generados son fuertes al principio y se van debilitando, con la recomendación actual de "reforzar" con una nueva dosis al cabo de tres o cuatro meses. (curiosamente, el discurso oficial es que ahora han disminuido los casos graves gracias a unas inyecciones que se hicieron hace seis meses o más ¿no contradice lo anterior?)</p> <p>Para intentar responder a la pregunta, he considerado periodos de tiempo simétricos en torno al comienzo de la "vacunación" o sea, un día antes y un día después, dos días antes y después, y así hasta 300 días antes y después del comienzo de las inyecciones. Al hacer tests estadísticos, se encuentra que no hay efecto significativo desde el punto de vista estadístico (p-value < 0.01) hasta pasados más de 140 días, y para periodos mayores de 140 días la conclusión es que hay más muertos COVID-19 durante la "vacunación" que antes (estadísticamente significativo con p-value < 0.01). Hasta los 140 días, los resultados son que no se puede descartar que mortalidad COVID-19 antes y después tienen la misma mediana y que, por tanto, son indistinguibles estadísticamente.</p> <p>En palabras llanas, no se nota diferencia hasta más o menos 140 días y después la conclusión clara es que hay más muertos COVID-19 durante la "vacunación" que antes (en 2020). Otra vez, la revista no puede decir que los cálculos son incorrectos, por lo que simplemente indican que "no es de interés". No sé si esta calificación sería compartida por la población en general. Evidentemente, para los gobernantes estos datos y resultados son bastante "incómodos".</p> <p>La mayor limitación de este pequeño estudio es el conjunto de datos de base. Se puede argumentar sobre su inexactitud. De hecho una de las mayores inexactitudes es la declaración de comienzo de la "vacunación". Muchos países estaban vacunando antes de la fecha que aparece en OWID. De hecho, estaban vacunando a personas de riesgo o personal sanitario y auxiliar en sitios como residencias. Ajustando estas fechas, los resultados serían todavía más desfavorables para los productos sanitario. Otro ejemplo es China, cuya declaración de mortalidad es simplemente nula a partir de una fecha. No he intentado correcciones, simplemente he tomado los datos como lo he hecho con todos los demás países. Otra de las posibles inexactitudes son las primeras olas en países europeos y algunos estados de USA, en las que un estado de panico general y otras causas posibles pudieron influir en una fuerte sobre diagnosis de COVID-19, especialmente en las residencias de ancianos. Tampoco he hecho ningún intento de corrección, sino que he tomado los datos tal cual. Habrá otras limitaciones de las que no soy consciente.</p> <p>El test utilizado es el "Wilkinson rank sum" que no asume una distribución parametrizada de los datos, por lo que podemos estar bastante seguros de que no estoy introduciendo trucos estadísticos. </p> <p><strong>Importante</strong>: no estoy hablando de muertes producidas/declaradas por vacunas, aunque muchos muertos COVID-19 estaban "vacunados" durante 2021. No es hasta fechas recientes que los gobiernos han comenzado a precisar el estado "vacunal" de los muertos COVID-19, fundamentalmente como parte de la campaña de acoso a las personas "no vacunadas". Parece que las estadísticas recientes no son favorables a la estrategia gubernamental, por lo que los datos se van cubriendo de un velo de misterio.</p> <p><strong>En conclusión, la comparación de la mortalidad COVID-19 antes y después del comienzo de la "vacunación" más masiva de la historia de la humanidad (hasta ahora) no permite afirmar que las "vacunas" han disminuido la mortalidad COVID-19 hasta la fecha de los datos recogidos de OWID.</strong></p> <p> </p> <p>***** ******* **********</p> <p>Content:</p> <p>Data downloaded from Our World in Data at January 07, 2022</p> <p>Source code for the analysis and visualization </p> <p>submitted figure </p> <p>submitted letter</p> <p>response from the journal</p>
Data for the journal article "Brown Carbon from Biomass Burning Imposes Strong Circum-Arctic Warming"
<p>The data for the 3 figures in the journal article "Brown Carbon from Biomass Burning Imposes Strong Circum-Arctic Warming"</p>
Supplementary scripts and data for Bastin et al.: Atlantic Equatorial Deep Jets in Argo Float Data, Journal of Physical Oceanography
<p>Analysis scripts used to obtain the results in the paper</p> <p>Bastin, S., M. Claus, P. Brandt and R. J. Greatbatch: Atlantic Equatorial Deep Jets in Argo Float Data. Submitted to Journal of Physical Oceanography.</p>
Code for noise-based seismic velocity changes estimation with the Bezymianny volcano data set. Journal of Volcanology and Geothermal Research.
<p>This file contains all the data and the python scripts used to estimate seismic velocity changes for the Bezymianny volcano (Klyuchevskoy volcano group). It also includes a guideline README.pdf with the description how to reproduce all the results presented in the paper <strong>Berezhnev Y., Belovezhets N., Shapiro N., Koulakov I. (2022), Temporal changes of seismic velocities below Bezymianny volcano prior to its explosive eruption on 20.12.2017, Journal of Volcanology and Geothermal Research</strong></p>
International Journal of Social Research Methods: 25th Anniversary Editorial bonus material (methods and data)
<p>This dataset accompanies the 25th Anniversary Editorial bonus material (methods and data) of the International Journal of Social Research Methods.</p> <p>https://www.tandfonline.com/journals/tsrm20/collections/TSRM_25th_Anniversary_SI</p>
Supplementary Data for "Adoption of Transparency and Openness Promotion (TOP) guidelines across journals"
<p>Supplementary data for: https://zenodo.org/record/7129250</p>
Data supplementing the article "Avoiding quantification bias in metabarcoding: application of a cell biovolume correction factor in diatom molecular biomonitoring" V. Vasselon, A. Bouchez, F. Rimet, S. Jacquet, R. Trobajo, M. Corniquel, K. Tapolczai, I. Domaizon submitted to Methods in Ecology and Evolution journal
<p>These data supplement the article "Avoiding quantification bias in metabarcoding: application of a cell biovolume correction factor in diatom molecular biomonitoring" V. Vasselon, A. Bouchez, F. Rimet, S. Jacquet, R. Trobajo, M. Corniquel, K. Tapolczai, I. Domaizon submitted to Methods in Ecology and Evolution journal</p> <p>The directory contains the following files:</p> <p>1<strong>5 fastq files raw reads (5 mock communities, 3 replicates)</strong><strong>.rar </strong>- contains the 15 fastq files provided by the sequencing platform with demultiplexed DNA reads (raw data prior any bioinformatics treatments).</p> <p><strong>15 fastq files information.xlsx</strong> :</p> <p>- contains the information relative to the 15 fastq files corresponding to the PGM raw data of the 5 mock communities (sequenced with 3 replicates), including: the ID of the fastq files, the mock community name, the replicate number, the final sample Id and the number of raw reads per fastq file.</p> <p>- contains the information of the proportion of the 8 diatoms species (%) used to create the 5 mock communities (estimated from microscopy).</p>
Data Set for the Journal Article "SCINE - Software for Chemical Interaction Networks"
<p>This data archive contains all data and software described and used in the following publication:</p> <p>Thomas Weymuth, Jan P. Unsleber, Paul L. Türtscher, Miguel Steiner, Jan-Grimo Sobez, Charlotte H.<br>Müller, Maximilian Mörchen, Veronika Klasovita, Stephanie A. Grimmel, Marco Eckhoff, Katja-Sophia<br>Csizi, Francesco Bosia, Moritz Bensberg, Markus Reiher, "SCINE --- Software for Chemical Interaction<br>Networks", in preparation.</p> <p>The directory structure is as follows:</p> <ul> <li>software: contains all software used for the example exploration <ul> <li>requirements.txt: lists all Python packages needed to create the virtual environment with which the exploration has been carried out; the virtual environment was created with Python 3.6.8.</li> <li>start.py: script to initialize the database with the reactants</li> <li>step_1.py: script to create the first set of reaction trials; after having set up the trials, execute the script "start.py" with the option "continue"</li> <li>step_2.py: script to create the second set of reaction trials; after having set up the trials, execute the script "start.py" with the option "continue"</li> <li>puffin_1.3.0.sif: Singularity image containing a full Puffin instance (version 1.3.0) to execute all calculations of the exploration</li> <li>submit_container.sh: script to submit the Puffin image to the queueing system</li> </ul> </li> <li>data: contains a complete dump of the database created during the example exploration; additionally, this directory contains a script called "import.sh" which can be used to reimport the data into a MongoDB instance</li> </ul>
MDM data for "Wind driven ocean circulation changes can amplify future cooling of the North Atlantic warming hole" - submitted to Journal of Climate
<p>Data files for MDM simulation used in Journal of Climate submission, "Wind driven ocean circulation changes can amplify future cooling of the North Atlantic warming hole"</p>
Supplemental Data for the Journal Article Entitled The mechanistic origins of heterogeneous void growth during ductile failure accepted for publication by Acta Materialia
<p>This repository contains the Supplemental Data for the Journal Article Entitled The mechanistic origins of heterogeneous void growth during ductile failure accepted for publication by Acta Materialia.</p> <p>Authors: M.W. Vaughan<sup>a</sup>, H. Lim<sup>a</sup>, B. Pham<sup>a</sup>, R. Seede<sup>a</sup>, A. T. Polonsky<sup> a</sup>, K. Johnson<sup> a</sup>, P. J. Noell<sup>a,*</sup></p> <p>a: Sandia National Laboratories, Albuquerque, NM 87123</p> <p>Each folder contains a ReadMe.txt describing the files and their organization within each folder. </p> <p><br>Acknowledgements:<br><span>This work was supported by the Laboratory Directed Research and Development program at Sandia National Laboratories, a multimission laboratory managed and operated by National Technology and Engineering Solutions of Sandia LLC, a wholly owned subsidiary of Honeywell International Inc. for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525. The views expressed in the article do not necessarily represent the views of the U.S. DOE or the United States Government. </span></p>
Source data for publication "A multimodal atlas of hepatocellular carcinoma reveals convergent evolutionary paths and 'bad apple' effect on clinical trajectory" in Journal of Hepatology
<p>Processed genomic and transcriptomic data for the publication <a href="https://doi.org/10.1016/j.jhep.2024.05.017">https://doi.org/10.1016/j.jhep.2024.05.017</a>.</p> <p>cnv_segmentation.tsv: CNV segmentation file from Sequenza.</p> <p>cnv_arm.tsv: Significant arm level CNV events called by GISTIC, from broad_values_by_arm.txt file.</p> <p>cnv_gene.tsv: Gene level CNV events called by GISTIC, from all_threshold_by_genes.txt file. </p> <p>RNA_raw_counts.tsv: Raw RNA-seq read counts from featureCounts.</p> <p>snv_indel.tsv: All SNV and Indel called with annotation from Funcotator.</p> <p> </p>
ScienceDex guides
Understand access before you commit
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.