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1,773 results for “Supplementary data,”
Supplementary File S2 for the publication 'Predicting Bacterial Virulence Factors - Evaluation of Machine Learning and Negative Data Strategies' by Rentzsch, R et al.
<p>Supplementary File S2 for the publication 'Predicting Bacterial Virulence Factors - Evaluation of Machine Learning and Negative Data Strategies' by Robert Rentzsch, Carlus Deneke, Andreas Nitsche, and Bernhard Y. Renard</p>
Supplementary Data for "FreeHi-C: high fidelity Hi-C data simulation for benchmarking and data augmentation"
<p>Simulated and processed data utilized in the paper "FreeHi-C: high fidelity Hi-C data simulation for benchmarking and data augmentation" for visualization and further analysis.</p>
Integrated Probabilistic Annotation (IPA): A Bayesian-based annotation method for metabolomic profiles integrating biochemical connections, isotope patterns and adduct relationships - Supplementary Data
<ol> <li>Supplementary_data_1: data and code for standards analysis and database update</li> <li>Supplementary_data_2.zip: data and code used for the generation of the synthetic experiment</li> <li>Supplementary_data_3.zip: data, code, and results of the <em>E. coli</em> dataset analysis</li> <li>Supplementary_data_4.zip: data, code, and results of the beer dataset analysis</li> <li>Supplementary_data_5.zip: data, code, and results of the comparison with xMSannotator</li> </ol>
SH component synthetic seismograms (SE_Supplementary_data)
<p>Includes synthetic data files generated with pseudospectral method. See README for file format details.</p>
The ecology of suburban juvenile European hedgehogs (Erinaceus europaeus). Supplementary data set for home range calculations.
<p>The complete data set on which we based the home range calculations on in our paper: The ecology of suburban juvenile European hedgehogs (Erinaceus europaeus) in Denmark, Ecology and Evolution.</p>
Supplementary Data for Massively Parallel Implicit Equal-Weights Particle Filter for Ocean Drift Trajectory Forecasting
<p>This data repository is provided as a supplement to the paper *Massively Parallel Implicit Equal-Weights Particle Filter for Ocean Drift Trajectory Forecasting* written by Håvard Heitlo Holm, Martin Lilleeng Sætra and Peter Jan van Leeuwen. It contains the complete datasets (initial conditions and results of the ensemble simulations) obtained from the experiments presented therein.</p> <p>This data set is generated by, and can be further post-processed and visualized by, the code published as *metno/gpu-ocean: Supplementary Software for Massively Parallel Implicit Equal-Weights Particle Filter for Ocean Drift Trajectory Forecasting* by Håvard Heitlo Holm, Martin Lilleeng Sætra and André Rigland Brodtkorb (DOI 10.5281/zenodo.3458291). </p> <p> </p>
Supplementary Data for "Identifying Promising Metal−Organic Frameworks for Heterogeneous Catalysis via High-Throughput Periodic Density Functional Theory"
<p>Supplementary data to accompany:</p> <p>A.S. Rosen, J.M. Notestein, R.Q. Snurr. "Identifying Promising Metal-Organic Frameworks for Heterogeneous Catalysis via High-Throughput Periodic Density Functional Theory", J. Comput. Chem (2019). DOI: 10.1002/jcc.25787</p>
Supplementary information for samples and data used in Salazar et al. (2019)
<p>Supplementary information for samples and data used in Salazar et al. (2019). <em>Gene expression changes and community turnover differentially shape the global ocean metatranscriptome</em>. https://doi.org/10.1016/j.cell.2019.10.014</p>
Supplementary data for the manuscript "Thermodynamic properties of isoprene and monoterpene derived organosulfates estimated with COSMOtherm"
<p>.cosmo and .energy files of various isoprene and monoterpene derived organosulfates and methyl bisulfate (neutral and deprotonated), IEPOX (neutral) and hydrated sodium (cation).</p>
Supplementary Data for "DNA hairpin base-flipping dynamics drives APOBEC3A recognition and selectivity"
<p>Contains CSV-formatted files with RMSD and Sugar Pucker averages and standard deviations for 3- and 4-nt hairpin loop simulations as described in the manuscript "DNA hairpin base-flipping dynamics drives APOBEC3A recognition and selectivity".</p>
Supplementary Data file 3
<p>Supplementary Data file 3 of Faust et al., "Adipocyte associated glucocorticoid signaling regulates normal fibroblast function which is lost in inflammatory arthritis" </p> <p>The mzdata files were used for the XCMS raw data output of the lipidomics analysis of SPE-chloroform fractions versus SPE-acetone fractions from the adipocyte conditioned media (ACM). The reversed phase HPLC-MS (negative ion mode) data were collected and converted to mzdata files and analyzed using R software (version 3.4.2) package XCMS (1.52.0), which reported m/z, retention time, fold change, p-value, and intensity for every data point (n=1,884).</p>
Supplementary data for: Graphene Microelectrode Arrays, 4D Structured Illumination Microscopy, and a Machine Learning Spike Sorting Algorithm Permit the Analysis of Ultrastructural Neuronal Changes During Neuronal Signalling in a Model of Niemann-Pick Disease Type C
<p>Supplementary example data for the work presented in "<em>Graphene Microelectrode Arrays, 4D Structured Illumination Microscopy, and a Machine Learning Spike Sorting Algorithm Permit the Analysis of Ultrastructural Neuronal Changes During Neuronal Signalling in a Model of Niemann-Pick Disease Type C</em>". </p> <p><strong>Abstract: </strong></p> <p>Simultaneously recording network activity and ultrastructural changes of the synapse is essential for advancing our understanding of the basis of neuronal functions. However, the rapid millisecond-scale fluctuations in neuronal activity and the subtle sub-diffraction resolution changes of synaptic morphology pose significant challenges to this endeavour. Here, we use specially designed graphene microelectrode arrays (G-MEAs), which are compatible with high spatial resolution imaging across various scales as well as permit high temporal resolution electrophysiological recordings to address these challenges. Furthermore, alongside G-MEAs, we have developed an easy-to-implement machine learning algorithm to efficiently process the large datasets collected from MEA recordings. We demonstrate that the combined use of G-MEAs, machine learning (ML) spike analysis, and four-dimensional (4D) structured illumination microscopy (SIM) enables monitoring the impact of disease progression on hippocampal neurons which have been treated with an intracellular cholesterol transport inhibitor mimicking Niemann-Pick disease type C (NPC), and show that synaptic boutons, compared to untreated controls, significantly increase in size, leading to a loss in neuronal signalling capacity.</p> <p> </p>
Metal(loid)s in urban soil from historical municipal solid waste landfill: Geochemistry, source apportionment, bioaccessibility testing and human health risks - Supplementary data
<p>This is a supplementary dataset to the paper:</p> <p>Hiller E., Faragó T., Kolesár M., Filová L., Mihaljevič M., Jurovič L., Demko R., Mchlica A., Štefánek J., Vítková M. (2024): Metal(loid)s in urban soil from historical municipal solid waste landfill: Geochemistry, source apportionment, bioaccessibility and human health risks. <em>Chemosphere</em> <strong>362</strong>, 142677. DOI: 10.1016/j.chemosphere.2024.142677</p> <p>This research was supported by the Johannes Amos Comenius Programme (OP JAC), project No. CZ.02.01.01/00/22_008/0004605, Natural and anthropogenic georisks. The dataset is published under the Creative Commons Attribution 4.0 International License (CC-BY-4.0). This license allows others to distribute, remix, adapt, and build upon the dataset for any purpose, even commercially, as long as they give appropriate credit to the original creator(s).</p>
N-glycosylation acts as a switch for FGFR1 trafficking between the plasma membrane and nuclear envelope - yet unpublished supplementary data regarding Fig. 1C
<p>Fibroblast growth factor receptor 1 (FGFR1) is a heavily N-glycosylated cell surface receptor tyrosine kinase that transmits signals across the plasma membrane, in response to fibroblast growth factors (FGFs). Balanced FGF/FGFR1 signaling is crucial for the development and homeostasis of the human body, and aberrant FGFR1 is frequently observed in various cancers. In addition to its predominant localization to the plasma membrane, FGFR1 has also been detected inside cells, mainly in the nuclear lumen, where it modulates gene expression. However, the exact mechanism of FGFR1 nuclear transport is still unknown. In this study, we generated a glycosylation-free mutant of FGFR1, FGFR1.GF, and demonstrated that it is localized primarily to the nuclear envelope. We show that reintroducing N-glycans into the D3 domain cannot redirect FGFR1 to the plasma membrane or exclude the receptor from the nuclear envelope. Reestablishment of D2 domain N-glycans largely inhibits FGFR1 accumulation in the nuclear envelope, but the receptor continues to accumulate inside the cell, mainly in the ER. Only the simultaneous presence of N-glycans of the D2 and D3 domains of FGFR1 promotes efficient transport of FGFR1 to the plasma membrane. We demonstrate that while disturbed FGFR1 folding results in partial FGFR1 accumulation in the ER, impaired FGFR1 secretion drives FGFR1 trafficking to the nuclear envelope. Intracellular FGFR1.GF displays a high level of autoactivation, suggesting the presence of nuclear FGFR1 signaling, which is independent of FGF. Using mass spectrometry and proximity ligation assay, we identified novel binding partners of the nuclear envelope-localized FGFR1, providing insights into its cellular functions. Collectively, our data define N-glycosylation of FGFR1 as an important regulator of FGFR1 kinase activity and, most importantly, as a switchable signal for FGFR1 trafficking between the nuclear envelope and plasma membrane, which, due to spatial restrictions, shapes FGFR1 interactome and cellular function.</p> <p> </p> <p>These data are raw data of Fig. 1C generated by Aleksandra Chorążewska. These data are not present in supplementary data od publication</p>
Identification of processes in Cu-ore heap leaching using Cu isotopes and leachate chemistry at Tschudi mine, northern Namibia - Supplementary data
<p>This is a supplementary dataset to the paper:</p> <p>Sracek O., Ettler V., Mihaljevič M., Kříbek B., Mapani B., Penížek V., Zádorová T., Vaněk A. (2024): Identification of processes in Cu-ore heap leaching using Cu isotopes and leachate chemistry at Tschudi mine, northern Namibia. <em>Hydrometallurgy</em> <strong>228</strong>, 106356.</p> <p>This research was supported by the Johannes Amos Comenius Programme (OP JAC), project No. CZ.02.01.01/00/22_008/0004605, Natural and anthropogenic georisks. The dataset is published under the Creative Commons Attribution 4.0 International License (CC-BY-4.0). This license allows others to distribute, remix, adapt, and build upon the dataset for any purpose, even commercially, as long as they give appropriate credit to the original creator(s).</p>
Ndufs4 knockout mice with isolated complex I deficiency engage a futile adaptive brain response - supplementary data
<p>This study aims to provide insight into the Leigh Syndrome pathomechanism at the sub-brain level. To this end, a comparative proteome analysis was performed on various brain regions of 6 wildtype (WT) and 6 whole body (WB) Ndufs4-/- (WB-KO) mice over two experiments. Samples were collected at six weeks after birth (i.e. ~ one week prior to WB-KO death). For the first experiment samples were collected from a brain slice (BrSl), which contained (parts of) the CC, HC, hypothalamus, thalamus, caudate putamen, and olfactory areas. For the second experiment the analysed brain regions consisted of cerebellum (CB), cerebral cortex (CC), hippocampus (HC), inferior colliculust (IC), and superior colliculus (SC).</p>
Supplementary data and code to "Cellular location shapes quaternary structure of enzymes" by György Abrusán and Aleksej Zelezniak
<p>Scripts and high-level data to reproduce the figures and supplementary figures of "Cellular location shapes quaternary structure of enzymes" by György Abrusán and Aleksej Zelezniak. <em>Nature Communications</em> (2024) 15:8505.</p>
Supplementary Data and Software for "Robust NLoS Localization in 5G mmWave Networks: Data-based Methods and Performance"
<p>The file includes supplementary data for "Robust NLoS Localization in 5G mmWave Networks: Data-based Methods and Performance". If you would like to re-use the software provided please cite the following two items.</p> <p>R. Klus, J. Talvitie, J. Equi, G. Fodor, J. Torsner, and M. Valkama, “Robust NLoS Localization in 5G mmWave Networks: Data-based Methods and<br>Performance,” IEEE Transactions on Vehicular Technology, 2024.</p> <p>R Klus et al. (2024). Supplementary materials for “Robust NLoS Localization in 5G mmWave Networks: Data-based Methods and Performance”. version v1, 25.06.2024, [Online]. Available: https://doi.org/10.5281/zenodo.12204892</p> <p>If you have any questions about this package, please do not hesitate to contact Roman Klus (roman.klus@tuni.fi).</p>
Supplementary Data associated with the article "LukProt: A database of eukaryotic predicted proteins designed for investigations of animal origins"
<p>Supplementary Data associated with the article "LukProt: A database of eukaryotic predicted proteins designed for investigations of animal origins" - BUSCO example.</p> <p> </p> <p>National Science Centre of Poland is acknowledged for funding of the project 2020/36/C/NZ8/00081, "The role of glycosylation in the emergence of animal multicellularity", which enabled the creation of this dataset.</p> <p> </p> <p> </p>
The supplementary test data of GeoNet
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.