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1,773 results for “Supplementary data,”
Habibpourmehraban et al Supplementary data file updated 25Nov2022
<p>Supplementary data for a publication submitted to International Journal of Molecular Sciences, Habibpourmehraban et al, November 2022. This version updated to also include raw data from parallel reaction monitoring experiments.</p>
Supplementary Data for 'A sensitive array for microRNA expression profiling (miChip) based on locked nucleic acids (LNA).'
<p>Supplementary Data for 'Castoldi, M., Schmidt, S., Benes, V., Noerholm, M., Kulozik, A.E., Hentze, M.W. and Muckenthaler, M.U., 2006. A sensitive array for microRNA expression profiling (miChip) based on locked nucleic acids (LNA). <em>Rna</em>, <em>12</em>(5), pp.913-920.'</p>
PySME - Paper Supplementary Data
<p>Synthetic spectra created for the paper "PySME - Spectroscopy Made Easier". For more information on the creation of these spectra, see the paper.</p> <p>Based on observations collected at the European Southern Observatory under ESO programs 60.A-9036(A), 192.C-0224(A), 083.C-0794(A), 072.C-0488(E), 288.C-5010(A), 0104.C-0849(A), and 098.C-0739(A).</p> <p> </p>
Use of Time Dependent Data in Bayesian Global 21cm Foreground and Signal Modelling (supplementary data)
<p>These are the posterior files, foreground simulation data sets and chromaticity factor values used to produce the results for <a href="https://arxiv.org/abs/2210.04707">arXiv:2210.04707</a>.</p> <p> </p> <p>A plotting script to reproduce key figures is included.</p> <p>Software used:</p> <ul> <li><a href="https://github.com/PolyChord/PolyChordLite/tree/839292290a7747dbee82933bb9f7f955ac45c3ca">PolyChord</a></li> <li><a href="https://github.com/williamjameshandley/fgivenx">fgivenx</a></li> </ul>
Supplementary Data and Code: Determinants of range sizes pinpoint vulnerability of groundwater species to climate change: a case study on subterranean amphipods from the Dinarides
<p>Supplementary Data and R code for phylogenetic analyses for manuscript entitled <em>Determinants of range sizes pinpoint vulnerability of groundwater species to climate change: a case study on subterranean amphipods from the Dinarides.</em></p> <p><strong>The dataset contains</strong></p> <p><em>beast.tree</em> → data for import into R: maximum credibility phylogeny<br> <em>data_lambert.csv</em> → data for import into R: data on habitat and distribution for 52 <em>Niphargus </em>species<br> <em>morpho.csv</em> → data for import into R: morphometric data (body length) for 52 <em>Niphargus </em>species<br> <em>niphargus_ranges.Rmd</em> → fully reproducible R markdown file<br> <em>niphargus_ranges.html </em>→ html output of Rmd file</p> <p>To be able to run the analysis put the data files into folder <data> and run the Rmd script.</p>
Supplementary data for A Systematic Literature Review on the Code Smells Datasets and Validation Mechanisms
<p>The attached Microsoft Excel files contain the data and diagrams of the paper:</p> <p><strong>A systematic literature review on the code smells datasets and validation mechanisms</strong></p> <p>The article is under review in the ACM Computing Surveys.</p> <p> </p>
Supplementary data of the paper 'Adaptive trends of sequence compositional complexity over pandemic time in the SARS CoV 2 coronavirus'
<p>Supplement of the paper<br> "Adaptive trends of sequence compositional complexity over pandemic time in the SARS-CoV-2 coronavirus”<br> During the spread of the COVID-19 pandemic, the SARS-CoV-2 coronavirus underwent mutation and recombination events that altered its genome compositional structure, thus providing an unprecedented opportunity to check an evolutionary process in real time. The mutation rate is known to be lower than expected for neutral evolution, suggesting natural selection and convergent evolution. We begin by summarizing the compositional heterogeneity of each viral genome by computing its Sequence Compositional Complexity (SCC). To analyze the full range of SCC diversity, we select random samples of high quality coronavirus genomes covering the full span of the pandemic. We then search for evolutionary trends that could inform us on the adaptive process of the virus to its human host by computing the phylogenetic ridge regression of SCC against time (i.e., the collection date of each viral isolate). In early samples, we find no statistical support for any trend in SCC values, although the viral genome appears to evolve faster than Brownian Motion (BM) expectation. However, in samples taken after the emergence of high fitness variants, and despite the brief time span elapsed, a driven decreasing trend for SCC and an increasing one for its absolute evolutionary rate are detected, pointing to a role for selection in the evolution of SCC in the coronavirus. We conclude that the higher fitness of variant genomes may have leads to adaptive trends of SCC over pandemic time in the coronavirus.</p> <p>Supplementary files</p> <table> <tbody> <tr> <td> <p><strong>File</strong></p> </td> <td> <p><strong>Description</strong></p> </td> </tr> <tr> <td> <p>SupplementaryTables S1-S19.zip</p> </td> <td> <p>Excel supplementary tables: The strain name, the collection date, and the SCC values for each analyzed genome.</p> </td> </tr> <tr> <td>nextstrain_ncov_open_global_timetree.nwk</td> <td>ML phylodynamic tree for the Nextstrain sample</td> </tr> <tr> <td> <p>SupplementaryTable S20.pdf</p> </td> <td> <p>A complete list acknowledging the authors, originating and submitting laboratories of the genetic sequences we used for the analysis of the Nextstrain sample.</p> </td> </tr> <tr> <td>Nextstrain_sample_fasta_3059.zip</td> <td>Nextstrain sample (sequences in Fasta format)</td> </tr> <tr> <td> <p>PhylogeneticTimetrees_NewickFormat.zip</p> </td> <td> <p>Phylogenetic timetrees (Newick format).</p> </td> </tr> </tbody> </table> <p> </p>
Supplementary Data to *Informative and adaptive distances and summary statistics in approximate Bayesian computation*
<p>Supplementary code and data to <strong>Informative and adaptive distances and summary statistics in approximate Bayesian computation</strong> by <strong>Y. Schaelte et al., 2021</strong>.</p> <p>The archive contains a <strong>README.rst </strong>for information on what is where and how to execute the study and generate the figures. The underlying code without the data can be found at the repository https://github.com/yannikschaelte/study_abc_slad, of which this archive is a snapshot.</p>
Supplementary material for "Including filter-feeding gelatinous macrozooplankton in a global marine biogeochemical model: model-data comparison and impact on the ocean carbon cycle"
<p>Supplementary material for "Including filter-feeding gelatinous macrozooplankton in a global marine biogeochemical model: model-data comparison and impact on the ocean carbon cycle". </p> <p>Clerc, C., Bopp, L., Benedetti, F., Vogt, M., and Aumont, O.: Including filter-feeding gelatinous macrozooplankton in a global marine biogeochemical model: model-data comparison and impact on the ocean carbon cycle, EGUsphere [preprint], https://doi.org/10.5194/egusphere-2022-1282, 2022.</p> <p>Three directories can be downloaded:</p> <p><strong>DataOBS</strong> : AtlantECO [WP2] – Traditional microscopy dataset – Thaliacea (Salpida+Doliolida+Pyromosomatida) abundance and biomass concentration data, presented in Clerc et al. (2022). </p> <p><strong>FigPaper </strong>: Source code and .nc files for the figures presented in Clerc et al. (2022) (https://doi.org/10.5194/egusphere-2022-1282). </p> <p><strong>MY_SRC_PISCES_NEMO_3.6 :</strong> Additional fortran routines for the compilation of PISCES-FFGM, the model developed for Clerc et al. (2022), from NEMO-3.6 (https://www.nemo-ocean.eu)</p>
Supplementary data for eEDM study (to be published) and thesis
<p>The full output data for the eEDM project.</p> <p>Contains 4 iterations with different settings and the study on the impact of a single phase. Each iteration has a separate folder.</p> <p>The results after running SPheno, FeynHiggs, MicrOMEGAS and our in-house codes are then saved to a .csv file. These files can be found here. Each .csv file contains columns describing the parameter or observable that is taken from the output file of the relevant software package. Names are assumed to be self-explanatory (e.g. mn1 for the mass of the first neutralino).</p> <p>FT refers to fine-tuning as defined in our own in-house code.</p> <p>More details can be obtained upon request.</p>
RDF version of the supplementary data from Shin, Hyun Kil and Seo et al. Meta-analysis of Daphnia magna nanotoxicity experiments in accordance with test guidelines. Environ. Sci.: Nano (2018)
<p>This is an RDF version of the dataset published by Shin, Hyun Kil and Seo et al. as a supplement of the study Meta-analysis of Daphnia magna nanotoxicity experiments in accordance with test guidelines. Environ. Sci.: Nano (2018).</p> <p>The original dataset is available online: <a href="https://ui.staging.kit.cloud.douglasconnect.com/dataexplorer?dataset=ab2bc1ee-99dc-4ddf-b1f9-9fdeb8a0f48c%3A1&q=%7B%7D">https://ui.staging.kit.cloud.douglasconnect.com/dataexplorer?dataset=ab2bc1ee-99dc-4ddf-b1f9-9fdeb8a0f48c%3A1&q=%7B%7D</a></p> <p>The original publication DOI: <a href="http://dx.doi.org/10.1039/C7EN01127J">http://dx.doi.org/10.1039/C7EN01127J</a></p> <p>GitHub repository of the datasets converted to RDF along with RML mappings: <a href="https://github.com/ammar257ammar/RDFied-datasets">https://github.com/ammar257ammar/RDFied-datasets</a></p>
Supplementary data for: Genomics of secondarily temperate adaptation in the only non-Antarctic icefish
<p class="MsoNormal">White-blooded Antarctic icefishes are an example of extreme biological specialization both to the chronic cold of the Southern Ocean and to life without hemoglobin. As a result, icefishes display derived physiology that limits them to the cold and highly oxygenated Antarctic waters. Despite these constraints, a single icefish species, the pike icefish <em>Champsocephalus esox</em>, is presently found in temperate South American waters. To study the genetic mechanisms underlying temperate adaptation in this species, we generated chromosome-level genome assemblies of both <em>C. esox</em> and its Antarctic sister species, <em>Champsocephalus gunnari</em>. The <em>C. esox </em>genome is similar in structure and organization to that of Antarctic icefishes. However, we observe evidence of chromosomal rearrangements, some of which coincide with regions of elevated genetic divergence in pike icefish populations. Our results show several key biological pathways under selection, including genes related to the mitochondria, iron transport, and light sensing, highlighting candidates behind temperate adaptation in this species. The <em>C. esox</em> genome also shows antifreeze glycoprotein pseudogenization, likely due to relaxed selection following ancestral escape from Antarctica. While the organization of the canonical antifreeze glycoprotein locus is conserved in both <em>C. esox</em> and <em>C. gunnari</em>, both<em> </em>species show a translocation of antifreeze genes, previously unobserved in notothenioids. Our results present the first genomic characterization of a secondarily temperate notothenioid to date and serve as a basis for understanding the group's adaptive potential against a rapidly changing Antarctic environment.</p>
Supplementary data for: "Towards automatic generation of control structures for Process Flow Diagrams (PFDs) with Artificial Intelligence"
<p>Uploaded on 20. February 2023</p> <p>This is the supplementary data for the publication</p> <p>"Towards automatic generation of control structures for Process Flow Diagrams (PFDs) with Artificial Intelligence" (2023) by Edwin Hirtreiter, Lukas Schulze Balhorn, Artur M. Schweidtmann</p> <p>Corresponding author: A. M. Schweidtmann, E-mail: a.schweidtmann@tudelft.nl<br> Delft University of Technology, Department of Chemical Engineering, Process Intelligence Group, Van der Maasweg 9, 2629 HZ Delft, The Netherlands</p> <p>The folder contains json files with the training (train), test (test), and augmented training (train_augm) data files. The json files contain syntetically generated SFILES. </p> <p>The pre-print of the manuscript is accessible at https://doi.org/10.48550/arXiv.2211.05583</p>
Supplementary data for the paper: "Bacteria-based self-healing concrete exposed to frost salt scaling"
<p>Supplementary data for the paper: “Bacteria-based self-healing concrete exposed to frost salt scaling”.<br> <br> Open data concerning experimental work. The paper presents the benefits of introducing a bacteria-based healing agent in concrete to enable self-healing, assessed under frost salt scaling conditions. Durability tests such as scaling, water permeability and chloride ingress were performed. In addition, a microstructural analysis based on mercury intrusion porosimetry (MIP), fluorescence microscopy, thin section analysis, scanning electron microscopy (SEM) and energy-dispersive X-ray (EDX) spectroscopy was performed. </p> <p> </p>
Supplementary data to: Internal anatomy of brachyuran crab from a Late Cretaceous methane seep and an overview of internal soft tissues in fossil decapod crustaceans
<p>001-Secretanella_sp_AAK_072019.zip - µCT scan data, 1.28 GB stack of DICOM images. High-resolution X-ray computed tomography (CT) scans of specimen ALMNH:Paleo:6522 were obtained at the Berkeley Preclinical Imaging Facility (UC Berkeley, California, USA) in July 2019 using a GE Healthcare eXplore Locus Micro CT Scanner. The specimen was scanned using a conebeam energy of 80 kV, a current of 450 µA, 2,000 ms exposure time, and no filter, resulting in a voxel resolution of 20.523 µm. Visualization and three-dimensional reconstruction of the resulting µCT data were performed using the open-source software 3D Slicer v.4.13.0 (Fedorov et al., 2012).</p> <p>Additional_images_gifs_3Dmodel.zip - archive containing 3 folders of additionnal images, video (gifs) and a 3D model (STL file) :</p> <p>- Addendum_Figure_3 : additional images / views to the figure 3 presented in the paper.</p> <p>- Gifs_3d_models : gifs and STL 3d model of the scanned specimen</p> <p>- Images_gifs_inc_gastric_musc : images, gifs and 3d model similar as in the other folders, but displaying potential gastric muscles</p>
Supplementary data for: Transcriptomics of mosaic brain differentiation underlying complex division of labor in a social insect
<p>Concerted developmental programming may constrain changes in component structures of the brain, thus limiting the ability of selection acting on individual brain compartments to form an adaptive mosaic independent of total brain size or body size. Measuring patterns of gene expression underpinning brain scaling in conjunction with anatomical brain atlases can aid in identifying influences of concerted and/or mosaic evolution. Species exhibiting exceptional size and behavioral polyphenisms provide excellent systems to test predictions of brain evolution models by quantifying brain gene expression. We examined patterns of brain gene expression in a remarkably polymorphic and behaviorally complex social insect, the leafcutter ant <em>Atta</em> <em>cephalotes</em>. Approximately ~50% of differential gene expression observed among three morphologically, behaviorally, and neuroanatomically differentiated worker size groups was attributable to body size, but we also found strong evidence of differential brain gene expression unexplained by worker morphological variation. Transcriptomic analysis identified patterns of gene expression not linearly correlated with worker size but rather, in some cases, mirroring neuropil scaling. Additionally, we observed enriched gene ontology terms associated with nucleic acid regulation, metabolism, neurotransmission, and sensory perception, further supporting a relationship between brain gene expression and worker social role. These findings demonstrate that differential brain gene expression among polymorphic workers is linked to behavioral and neuroanatomical differentiation underpinning complex agrarian division of labor in <em>A</em>. <em>cephalotes</em>.</p>
Supplementary data and code to "Known allosteric proteins have central roles in genetic disease" by G. Abrusan, D. Ascher and M. Inouye, PLOS Computational Biology 18(2):e1009806.
<p>Scripts and data to reproduce the figures and supplementary figures of "G. Abrusan, D. Ascher and M. Inouye (2022) Known allosteric proteins have central roles in genetic disease." PLOS Computational Biology 18(2):e1009806. https://doi.org/10.1371/journal.pcbi.1009806.</p>
Supplementary data for the manuscript entitled "Evolution of the convective boundary layer in a WRF simulation nested down to 100 m resolution during a cloud-free case of LAFE 2017 and comparison to observations" (JGR Atmospheres)
<p>This dataset contains additional material to reproduce the simulation and some of the figures of the manuscipt entitled "Evolution of the convective boundary layer in a WRF simulation nested down to 100 m resolution during a cloud-free case of LAFE 2017 and comparison to observations" in the Journal of Geophysical Reasseach - Atmospheres.</p>
Supplementary Material 7 including Salamandra salamandra occurrence data, topographic, geological and land cover data and node-based resistances
<p>Supplementary material for the article "Habitat connectivity supports the local abundance of fire salamanders (Salamandra salamandra) but also the spread of Batrachochytrium salamandrivorans" by Bolte <em>et al</em>. (2023) published in Landscape Ecology (DOI: 10.1007/s10980-023-01636-8)</p> <p>This folder comprises a .shp file with fire salamander occurrences, topographic and land cover data (GeoTiff) from the northern Eifel region as well as the R Code used for the statistical analysis of salamander habitat suitability and connectivity.</p>
CESM and FOCI model data as supplementary data for Climate Index Collection based on model data (CICMoD)
<p>The Community Earth System Model (CESM) and the Flexible Ocean and Climate Infrastructure (FOCI) are both fully-coupled, global climate models that provide state-of-the-art computer simulations of the Earth's past, present, and future climate states.</p> <p>This dataset contains results from control runs with conditions of year 1850 without additional external forcing for 1000 years and 999 years for FOCI and CESM, respectively.</p> <p>Included features are:</p> <ul> <li>sea surface temperature</li> <li>surface air temperature</li> <li>sea level pressure</li> <li>sea surface salinity</li> <li>geopotential height (500mb)</li> <li>precipitation</li> </ul>
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.