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264 results for “Single molecule”
Single molecule experimental data for dwell time histogram in Gilburt et al, Angewandte Chemie 2017
<p>Raw and partially processed data for the dwell time histogram in the following publication:</p> <p>James A H Gilburt, Hajrah Sarkar, Peter Sheldrake, Julian Blagg, Liming Ying, Charlotte A Dodson (2017) Dynamic equilibrium of the Aurora-A kinase activation loop revealed by single molecule spectroscopy. <em>Angewandte Chemie</em></p> <p><strong><em>Please cite our publication in any use of this data</em></strong></p>
Multi-cell type deconvolution using a probabilistic model for single-molecule DNA methylation haplotypes
<p>Files required to run deconvolution with CelFIE-ISH and Epistate, in U250 regions from Loyfer et al. 2023, in both "pat" and "epiread" formats. </p>
Reference data and analysis software for "Four-color single-molecule imaging with engineered tags resolves the molecular architecture of signaling complexes in the plasma membrane"
<p>Reference data set for the single molecule co-tracking analysis presented in "Four-color single-molecule imaging with engineered tags resolves the molecular architecture of signaling complexes in the plasma membrane". Corresponding author for further inquiries:</p> <p>Prof. Dr. Jacob Piehler</p> <p>University of Osnabrück, Department of Biology/Chemistry, Division of Biophysics, Barbarastr. 11, 49076 Osnabrück, Germany</p> <p>https://www.biophysik.uni-osnabrueck.de/</p>
SupportingDataset Identification and Quantification of Within-Burst Dynamics in Singly-Labeled Single-Molecule Fluorescence Lifetime Experiments
<p>The Jupyter notebooks and resulting files used to demonstrate divisor-based mpH<sup>2</sup>MM. The analysis is demonstrated with both simulations and analyses of alpha-synuclein.</p> <ol> <li> <p><em><strong>Notebooks.zip</strong></em>:* Zip file containing the Jupyter notebooks for producing, analyzing and visualizing the simulated photon trajectories. Note: this folder contains all code needed to reproduce simulations. All other files related to the simulations are produced by one of the notebooks in this trajectory. However, as simulations can take a long time, the various results files are included in this repository so that notebooks can be run from intermediate steps.</p> <ol> <li> <p><strong>1-PIFE-pybromo-sims.ipynb</strong> : The code for producing simulated diffusion trajectories and photon-HDF5 files of two-state systems undergoing transition dynamics (the results of this notebook are stored in the sub-folder <em>PyBroMo_photonHDF5</em>)</p> </li> <li> <p><strong>2-PIFE-mpH2MM-sim-[lifetime components].ipynb </strong>: Notebooks performing divisor-based mpH<sup>2</sup>MM on simulated datasets for a given combination of lifetime states. (these notebooks store files that are contained in the sub-folder <em>H2MMresults</em>)</p> </li> <li> <p><strong>3-PIFE-mpH2MM-compiled-plots.ipynb</strong> : Jupyter notebook for producing figures comparing all results globally</p> </li> <li> <p><strong>532nm_IRF_19-10-2021.csb</strong>: the file containing the experimental IRF used in the simulations</p> </li> </ol> </li> <li> <p><em><strong>PyBroMo_photonHDF5.zip</strong></em>:* Zip file containing the simulated results of <em>1-PIFE-pybromo-sims</em> notebook as photon-HDF5 files (1 file per transition rate/lifetime combination)</p> </li> <li> <p><strong>PIFE-sim-dynamicmix_[lifetime components]_result.hdf5</strong>: special HDF5 files containing the results of each notebook in <em>Notebooks</em>, which are used by <em>3-PIFE-mpH2MM-compiled-plots</em></p> </li> <li> <p><strong>PIFE-mpH2MM-alpha-syn-vFinal.ipynb</strong>: divisor-based mpH<sup>2</sup>MM analysis of alpha-synuclein smPIFE data</p> </li> <li> <p><strong>H2MM-Lifetime_example.ipynb</strong>: A demonstration of divisor-based mpH<sup>2</sup>MM using nsALEX-smFRET data. This method could potentially demonstrate states differentiated in lifetimes independently of potential changes in E & S.</p> </li> <li> <p><strong>Template_ltH2MM.ipynb</strong>: An easy-to-follow implementation of divisor-based mpH<sup>2</sup>MM demonstrated on a single alpha-synuclein experimental data acquisition file. This can be used for learning how to implement and analyze single dye fluorescence lifetime data with mpH<sup>2</sup>MM</p> </li> </ol> <p> </p> <p>* For running these notebooks, generally, all files in <em>PyBroMo_photonHDF5.zip</em> should be placed into a single directory (i.e., the files in <em>Notebooks</em>.<em>zip</em> should be placed into the same directory as the files in <em>PyBroMo_photonHDF5</em>.<em>zip</em>) as the notebooks are set to read in files from their current directory.</p>
Enabling spectrally resolved single-molecule localization microscopy at high emitter densities: Dataset
<p>The data in this dataset accompanies the various figures present in the publication 'Enabling spectrally resolved single-molecule localization microscopy at high emitter densities'. Contained are tiff files used to create the figures 2-4 and Supplementary figures 1 and 2, as well as csvs after processed with the steps described in the paper (and contained in protocol text files).</p>
Long-Term, Single-Molecule Imaging of Proteins in Live Cells with Photoregulated Fluxional Fluorophores
<p>Supporting data for paper "Long-Term, Single-Molecule Imaging of Proteins in Live Cells with Photoregulated Fluxional Fluorophores"</p>
Single molecule, full-length transcript sequencing provides insight into the extreme metabolism of ruby-throated hummingbird Archilochus colubris
<p>Hummingbirds can support their high metabolic rates exclusively by oxidizing ingested sugars, which is unsurprising given their sugar-rich nectar diet and use of energetically expensive hovering flight. However, they cannot rely on dietary sugars as a fuel during fasting periods, such as during the night, at first light, or when undertaking long-distance migratory flights, and must instead rely exclusively on onboard lipids. This metabolic flexibility is remarkable both in that the birds can switch between exclusive use of each fuel type within minutes and in that de novo lipogenesis from dietary sugar precursors is the principle way in which fat stores are built, sometimes at exceptionally high rates, such as during the few days prior to a migratory flight. The hummingbird hepatopancreas is the principle location of de novo lipogenesis and likely plays a key role in fuel selection, fuel switching, and glucose homeostasis. Yet understanding how this tissue, and the whole organism, achieves and moderates high rates of energy turnover is hampered by a fundamental lack of information regarding how genes coding for relevant enzymes differ in their sequence, expression, and regulation in these unique animals. To address this knowledge gap, we generated a de novo transcriptome of the hummingbird liver using PacBio full-length cDNA sequencing (Iso-Seq), yielding a total of 8.6Gb of sequencing data, or 2.6M reads from 4 different size fractions. We analyzed data using the SMRTAnalysis v3.1 Iso-Seq pipeline, including classification of reads and clustering of isoforms (ICE) followed by error-correction (Arrow). We performed orthology analysis to identify closely related sequences between our transcriptome and other avian and human gene sets. We also aligned our transcriptome against the Calypte anna genome where possible. Finally, we closely examined homology of critical lipid metabolic genes between our transcriptome data and avian and human genomes. We confirmed high levels of sequence divergence within hummingbird lipogenic enzymes, suggesting a high probability of adaptive divergent function in the lipogenic liver pathways. Our results have leveraged cutting-edge technology and a novel bioinformatics pipeline to provide a compelling first direct look at the transcriptome of this incredible organism.</p>
Single-molecule FRET reveals multiscale chromatin dynamics modulated by HP1α-Fig. 1df
<p>smTIRF-FRET Data for Fig 1, for "Single-molecule FRET reveals multiscale chromatin dynamics modulated by HP1α"</p>
Data for "Atomic-scale perspective on individual thiol-terminated molecules anchored to single S vacancies in MoS2"
<p>This repository provides the original datasets for the manuscript "Atomic-scale perspective on individual thiol-terminated molecules anchored to single S vacancies in MoS2". It includes the original experimental data as well as the iPython Notebooks used to treat it in "<a href="../api/records/10160204/draft/files/Data_and_Analysis.zip/content" target="_blank" rel="noopener noreferrer">Data_and_Analysis.zip</a>" (see readme in individual folders for precise information), the datasets for the structure search and molecular dynamics calculations in "<a href="../api/records/10160204/draft/files/structure_search_and_MD.zip/content" target="_blank" rel="noopener noreferrer">structure_search_and_MD.zip</a>", as well as the data for the DFT calculations for the projected electronic density of states (PDoS) and the orbital densities of Fig.5 and 8 in "<a href="../api/records/10160204/draft/files/fig5.zip/content" target="_blank" rel="noopener noreferrer">fig5.zip</a>" and "<a href="../api/records/10160204/draft/files/fig8.zip/content" target="_blank" rel="noopener noreferrer">fig8.zip</a>", respectively.</p> <p> </p>
Nanotiming: single-molecule based, telomere-to-telomere DNA replication timing profiling by nanopore sequencing
<p>Dataset for the manuscript "Nanotiming: telomere-to-telomere DNA replication timing profiling by nanopore sequencing" by Theulot et al ,2024 (<span>https://doi.org/10.1038/s41467-024-55520-3</span>) related to the github repository (https://github.com/LacroixLaurent/NanoTiming)</p> <ul> <li>WT_rep3.tar.gz contains fast5 file from an experiment where yeast BT1 strain was grown for one doubling time with 5µM BrdU then DNA was sequenced on R9.4.1 ONT flowcell</li> <li>mod_mapping.bam contains the bam file resulting from the BrdU base calling with megalodon (v2.2.9) using our BT1 reference genome and our BrdU aware model for base-calling</li> <li>WT_rep3_nanoT.bed.gz contains the reads coordinates from the mod_mappings file</li> <li>WT_rep3_nanoT_alldata.rds contains the BrdU profiles for each reads of the mod_mappings file, with the BrdU signal binned in 1kb non overlaping windows</li> <li>WT_rep3_nanoT.rds contains the genomic BrdU signal profiles by 1kb non overlaping windows</li> <li>TeloLengthDataNanoT.rds contains all the telomeric sequences extracted from the experiments reported in the Figure 4 and S19 to S23 of the manuscript with the associated filtering information and nanotiming signal.</li> </ul> <p> </p>
Datasets for "Precision and accuracy of single-molecule FRET measurements – a multi-laboratory benchmark study"
<p>Supplementary material (raw data) for Fig. 2 in "<strong>Precision and accuracy of single-molecule FRET measurements – a multi-laboratory benchmark study</strong>" to be published with Nature Methods</p> <p>The confocal data is given in ht3 and hdf5 format.</p> <p>For the TIRF data the original TIFF-stacks are uploaded including the calibration files.</p>
Single molecule data for unphosphorylated Aurora-A (Gilburt et al, Chemical Science 2019)
<p>Raw and partially processed single molecule intensity histogram and dwell time histogram data for the following publication:</p> <p>James A H Gilburt, Paul Girvan, Julian Blagg, Liming Ying, Charlotte A Dodson (2019) Ligand discrimination between active and inactive activation loop conformations of Aurora-A kinase is unmodified by phosphorylation. Chemical Science. DOI: 10.1039/c8sc03669a</p> <p><strong><em>Please cite our publication in any use of this data.</em></strong></p> <p> </p>
Benchmarking Smartphone Fluorescence-Based Microscopy with DNA Origami Nanobeads: Reducing the Gap toward Single-Molecule Sensitivity
<p>Smartphone-based fluorescence microscopy has been rapidly developing over the last few years, enabling point-of-need detection of cells, bacteria, viruses, and biomarkers. These mobile microscopy devices are cost-effective, field-portable, and easy to use, and benefit from economies of scale. Recent developments in smartphone camera technology have improved their performance, getting closer to that of lab microscopes. Here, we report the use of DNA origami nanobeads with predefined numbers of fluorophores to quantify the sensitivity of a smartphone-based fluorescence microscope in terms of the minimum number of detectable molecules per diffraction-limited spot. With the brightness of a single dye molecule as a reference, we compare the performance of color and monochrome sensors embedded in state-of-the-art smartphones. Our results show that the monochrome sensor of a smartphone can achieve better sensitivity, with a detection limit of ∼10 fluorophores per spot. The use of DNA origami nanobeads to quantify the minimum number of detectable molecules of a sensor is broadly applicable to evaluate the sensitivity of various optical instruments.</p>
Systematic assessment of burst impurity in confocal-based single-molecule fluorescence detection using Brownian motion simulations - photon timetag simulation files
<p>Attached are the photon timestamp and channels simulated for different 3D diffusing molecules simulations at different conditions (simulation was performed by PyBroMo).</p> <p>Each of the files has, in its name, a code. The meaning of the codes are as following:</p> <pre>f32445 - 15 molecules at a concentration of 62 pM, with a diffusion coefficient of 90 micron^2/s - 60 second simulation using a numerical PSF model </pre> <pre>a01f8f - 15 molecules at a concentration of 31 pM, with a diffusion coefficient of 90 micron^2/s - 60 second simulation using a numerical PSF model</pre> <pre>9ff667 - 15 molecules at a concentration of 15.5 pM, with a diffusion coefficient of 90 micron^2/s - 60 second simulation using a numerical PSF model</pre> <pre>71154a - 15 molecules at a concentration of 62 pM, with a diffusion coefficient of 22.5 micron^2/s - 60 second simulation using a numerical PSF model</pre> <pre>ad926d - 15 molecules at a concentration of 62 pM, with a diffusion coefficient of 5.625 micron^2/s - 60 second simulation using a numerical PSF model</pre> <pre>1ab235 - 15 molecules at a concentration of 62 pM, with a diffusion coefficient of 90 micron^2/s - 180 second simulation using a numerical PSF model</pre> <pre>d00978 - 15 molecules at a concentration of 62 pM, with a diffusion coefficient of 5.625 micron^2/s - 180 second simulation using a numerical PSF model</pre> <p> </p> <pre>2469bb - 15 molecules at a concentration of 62 pM, with a diffusion coefficient of 90 micron^2/s - 60 second simulation using a Gaussian PSF model </pre> <pre>4be121 - 15 molecules at a concentration of 31 pM, with a diffusion coefficient of 90 micron^2/s - 60 second simulation using a Gaussian PSF model</pre> <pre>a7088f - 15 molecules at a concentration of 15.5 pM, with a diffusion coefficient of 90 micron^2/s - 60 second simulation using a Gaussian PSF model</pre> <pre>023983 - 15 molecules at a concentration of 62 pM, with a diffusion coefficient of 22.5 micron^2/s - 60 second simulation using a Gaussian PSF model</pre> <pre>653f61 - 15 molecules at a concentration of 62 pM, with a diffusion coefficient of 5.625 micron^2/s - 60 second simulation using a Gaussian PSF model</pre> <pre>4f06ee - 15 molecules at a concentration of 62 pM, with a diffusion coefficient of 90 micron^2/s - 180 second simulation using a Gaussian PSF model</pre> <pre>dec32c - 15 molecules at a concentration of 62 pM, with a diffusion coefficient of 5.625 micron^2/s - 180 second simulation using a Gaussian PSF model</pre> <p> </p> <pre>85b0a1 - 15 molecules at a concentration of 62 pM, with a diffusion coefficient of 90 micron^2/s , 10 of which belong to a sub-population with a mean FRET efficiency of 0.75, and the leftover 5 belong to another sub-populations with a mean FRET efficiency of 0.50 - 60 second simulation using a Numerical PSF model</pre> <pre>964ef3 - 15 molecules at a concentration of 62 pM, with a diffusion coefficient of 90 micron^2/s , 10 of which belong to a sub-population with a mean FRET efficiency of 0.75, and the leftover 5 belong to another sub-populations with a mean FRET efficiency of 0.50 - 180 second simulation using a Numerical PSF model</pre> <p> </p> <pre>f28f6e - 15 molecules at a concentration of 62 pM, with a diffusion coefficient of 90 micron^2/s , 10 of which belong to a sub-population with a mean FRET efficiency of 0.75, and the leftover 5 belong to another sub-populations with a mean FRET efficiency of 0.50 - 60 second simulation using a Gaussian PSF model</pre> <pre>c311dd - 15 molecules at a concentration of 62 pM, with a diffusion coefficient of 90 micron^2/s , 10 of which belong to a sub-population with a mean FRET efficiency of 0.75, and the leftover 5 belong to another sub-populations with a mean FRET efficiency of 0.50 - 180 second simulation using a Gaussian PSF model</pre>
3D super-resolution datasets associated with the paper "Whole-cell multi-target single-molecule super-resolution imaging in 3D with microfluidics and a single-objective tilted light sheet"
<p>3D single-molecule super-resolution datasets corresponding to reconstructions shown in <em>Whole-cell multi-target single-molecule super-resolution imaging in 3D with microfluidics and a single-objective tilted light sheet</em> by Saliba & Gagliano, Gustavsson et. al.</p>
Datasets and scripts for: Single-Molecule Dynamic Structural Biology with Vertically Arranged DNA on a Fluorescence Microscope
<p>The folder contains raw datasets (.ptu files) together with scripts and relevant results to reproduce the figures' plots of: "Single-Molecule Dynamic Structural Biology with Vertically Arranged DNA on a Fluorescence Microscope". </p>
Datasets for: Fullerene-based Single Molecule Diodes with Huge Rectification Ratios: A DFT-NEGF Study
<p>Input files and main output files for the study "Fullerene-based Single Molecule Diodes with Huge Rectification Ratios: A DFT-NEGF Study"</p>
Dataset for the paper High durability and stability of 2D nanofluidic devices for long-term single-molecule sensing
<p>Information regarding the Dataset, corresponding to the paper: “Thakur, M., Cai, N., Zhang, M. et al. High durability and stability of 2D nanofluidic devices for long-term single-molecule sensing. npj 2D Mater Appl 7, 11 (2023). https://doi.org/10.1038/s41699-023-00373-5”</p> <p>This folder contains the raw data and complete package of codes used to analyze, view, save, and plot data for the publication titled "High durability and stability of 2D nanofluidic devices for long-term single-molecule sensing". The code folder, "OpenNanopore-nanopore-tools", can be used to plot raw data which corresponds to the figures in the paper and supplementary information. </p>
Datasets underlying the paper Zero-mode waveguide nanowells for single-molecule detection in living cells
<p>Different datasets underlying the paper Zero-mode waveguide nanowells for single-molecule detection in living cells. The repository contains .zip archives, mostly containing a readme file with additional information.</p> <pre>Cell imaging experiments.zip contains the raw image files acquired on arrays of version 1 or version 2 using a Nikon TI inverted microscope and used in figures 4-6. </pre> <p>Gla_0127_14.zip contains SEM images of the fabrication of arrays of version 1</p> <p>Gla_29_Pd_1.zip contains SEM images of the fabrication of arrays of version 2</p> <p>SM experiments.zip contains the raw single-molecule fluorescence data acquired on an array of version 1 using a PicoQuant Microtime microscope together with the analysis files.</p> <p>FDTD simulations.zip contains the simulation files for the use in the software Lumerical</p>
Imaging data from "Live-cell 3D single-molecule tracking reveals modulation of enhancer dynamics by NuRD"
<p>3D 20ms, 3D 500ms and 2D dCas9 raw videos, localisation, tracking and trajectory analysis data</p> <p>From 'Live-cell 3D single-molecule tracking reveals modulation of enhancer dynamics by NuRD" (2021). Biorxiv. https://doi.org/10.1101/2020.04.03.003178</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.