Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
15
datasets available to search
ShareScore release 0.9.0
Dataset results
15 results for “time lapse microscopy”
Time-lapse 3D confocal microscopy videos of mitochondrial dynamics in human alveolar epithelial cells (A549-DsRed) infected with Mycobacterium marinum (Mmar) strains
<div>The dataset consists of time-lapse, 3D confocal images of mitochondrial dynamics in human alveolar epithelial cells (A549-DsRed) infected with Mycobacterium marinum (Mmar) strains. Images were captured at 60X magnification in an environmental chamber at 35°C for live-cell imaging. Host cell mitochondria were labeled with red fluorescent protein (RFP) and infected with both wildtype (wt) and ESAT-6 operon knockout mutant labeled with green fluorescent protein (GFP) at MOI of 100 for 24 hours at 35°C. Infected cells were identified and analyzed to explore the effect of pathogenic mycobacteria on mitochondrial morphology over time.</div> <div> </div> <div>More details available in this preprint: <a href="https://doi.org/10.48550/arXiv.2411.06035">https://doi.org/10.48550/arXiv.2411.06035</a></div>
BioTISR: a time-lapse biological image dataset for super-resolution microscopy
<p>BioTISR is a biological image dataset for super-resolution microscopy, currently including 2D and 3D time-lapse image pairs of low-and-high resolution images of a variety of biology structures, aiming to provide a high-quality dataset of time-lapse biological SR images for the community to spark more developments of computational SR methods.</p> <p>At present, 2D dataset includes five specimens (clathrin-coated pits, lysosomes, outer mitochondrial membrane, microtubules, and F-actin) acquired with the GI/TIRF-SIM mode and nonlinear SIM mode of our Multi-SIM system, and 3D dataset includes three specimens (outer mitochondrial membrane, microtubules, and F-actin) acquired with 3D-SIM mode of the Multi-SIM system. For each type of specimen and each imaging modality, we acquired the raw data from at least 50 distinct regions-of-interest (ROI). For each ROI, we acquired two (3D data) or three (2D data) groups of N-phase × M-orientation × T-timepoint raw images with a constant exposure time but increasing the excitation light intensity, where (N, M, T) are (3, 3, 20) for TIRF-SIM and GI-SIM, (5, 5, 10) for nonlinear SIM, and (3, 5, 10) for 3D-SIM. Specific imaging conditions and scripts for reading MRC file are provided in Supplement Files.</p> <p>The BioTISR dataset is related to the following paper:<a href="https://www.nature.com/articles/s41587-025-02553-8#citeas">Qiao, C., Liu, S., Wang, Y. <em>et al.</em> A neural network for long-term super-resolution imaging of live cells with reliable confidence quantification. <em>Nat Biotechnol</em> (2025). https://doi.org/10.1038/s41587-025-02553-8</a>, which is an extension of our previously published <a href="https://doi.org/10.6084/m9.figshare.13264793.v9">BioSR dataset</a> (https://www.nature.com/articles/s41592-020-01048-5).</p> <p>Limited by quota, the original images uploaded in the current 3D dataset are wide-field images obtained after averaging 15 images, where (N, M, T) are (1, 1, 10). We will update them to raw SIM images after the quota is expanded.</p> <p>2D dataset's url:</p> <p><a href="https://doi.org/10.5281/zenodo.13843670" target="_blank" rel="noopener">https://doi.org/10.5281/zenodo.13843670</a></p> <p>3D dataset's urls:</p> <p>F-actin:</p> <p>WF input: <a href="https://doi.org/10.5281/zenodo.13843673">https://doi.org/10.5281/zenodo.13843673</a></p> <p>Raw SIM input:<a href="https://doi.org/10.5281/zenodo.13994464" target="_blank" rel="noopener">https://doi.org/10.5281/zenodo.13994464</a></p> <p>Microtubules:</p> <p>WF input: <a href="https://doi.org/10.5281/zenodo.13932988" target="_blank" rel="noopener">https://doi.org/10.5281/zenodo.13932988</a></p> <p>Raw SIM input: <a href="https://doi.org/10.5281/zenodo.13989327" target="_blank" rel="noopener">https://doi.org/10.5281/zenodo.13989327</a></p> <p>Mitochondria:</p> <p>WF input: <a href="https://doi.org/10.5281/zenodo.13843183" target="_blank" rel="noopener">https://doi.org/10.5281/zenodo.13843183</a></p> <p>Raw SIM input: <a href="https://doi.org/10.5281/zenodo.14000502" target="_blank" rel="noopener">https://doi.org/10.5281/zenodo.14000502</a></p> <p> </p> <p>Update 2025.5.6</p> <p>Add optical transfer function(OTF) of the microscopy system and the pixel size of each data to the supplementary files.</p>
Strain gauge platforms: Time-lapse microscopy dataset of engineered cardiac microbundles
<p>This dataset is a "part I" extension of the "<a href="https://doi.org/10.5061/dryad.5x69p8d8g">Engineered cardiac microbundle time-lapse microscopy image dataset</a>" and contains 732 experimental time-lapse image sequences of beating hiPSC-based cardiac microbundles using microbundle strain gauge platforms [1] ("Type1"). In the "part II" extension, we included 808 experimental time-lapse image sequences of beating hiPSC-based cardiac microbundles using FibroTUG platforms [2] ("Type2"). </p> <p>References:</p> <p>[1] Zhang, K., Cloonan, P. E., Sundaram, S., Liu, F., Das, S. L., Ewoldt, J. K., ... & Chen, C. S. (2021). Plakophilin-2 truncating variants impair cardiac contractility by disrupting sarcomere stability and organization. <em>Science Advances</em>, <em>7</em>(42), eabh3995.</p> <p>[2] DePalma, S. J., Davidson, C. D., Stis, A. E., Helms, A. S., & Baker, B. M. (2021). Microenvironmental determinants of organized iPSC-cardiomyocyte tissues on synthetic fibrous matrices. <em>Biomaterials science</em>, <em>9</em>(1), 93-107.</p>
Time-lapse (4D) volumetric fluorescence microscopy image sequence of a living zebrafish embryo
<p>The dataset contains a time-lapse (4D) volumetric fluorescence microscopy image sequence of a living zebrafish embryo (cxcr4aMO). The sequence has been captured with a confocal laser-scanning microscope during zebrafish gastrulation and shows endodermal cells that have been fluorescently labelled.</p> <p>The sequence is best viewed with Fiji (https://fiji.sc/) and can be loaded into Matlab with tiffread.m (http://www.cytosim.org/misc/index.html).</p> <p>For the treatment of the specimen see:</p> <p>S. Nair and T. F. Schilling. Chemokine signaling controls endodermal migration during zebrafish gastrulation. Science, 322(5898):89–92, October 2008.</p>
Engineered cardiac microbundle time-lapse microscopy image dataset
<p>The "Microbundle Time-lapse Dataset" contains 24 experimental time-lapse images of cardiac microbundles using three distinct types of experimental testbed of beating lab grown hiPSC-based cardiac microbundles. Of the 24 experimental time-lapse images, 23 examples are brightfield videos, and a single example is a phase contrast video. We categorize the different experimental testbeds into 3 types, where "Type 1" includes movies obtained from standard experimental microbundle platforms termed microbundle strain gauges [1,2,3]. We refer to data collected from non-standard platforms termed FibroTUGs [4] as "Type 2" data, and "Type 3" data represents a highly versatile and diverse nanofabricated experimental platform [5,6].</p> <p><strong>References:</strong></p> <p>[1] Boudou T, Legant WR, Mu A, Borochin MA, Thavandiran N, Radisic M, Zandstra PW, Epstein JA, Margulies KB, Chen CS. A microfabricated platform to measure and manipulate the mechanics of engineered cardiac microtissues. Tissue Engineering Part A. 2012 May 1;18(9-10):910-9.</p> <p>[2] Xu F, Zhao R, Liu AS, Metz T, Shi Y, Bose P, Reich DH. A microfabricated magnetic actuation device for mechanical conditioning of arrays of 3D microtissues. Lab on a Chip. 2015;15(11):2496-503.</p> <p>[3] Bielawski KS, Leonard A, Bhandari S, Murry CE, Sniadecki NJ. Real-time force and frequency analysis of engineered human heart tissue derived from induced pluripotent stem cells using magnetic sensing. Tissue Engineering Part C: Methods. 2016 Oct 1;22(10):932-40.</p> <p>[4] DePalma SJ, Davidson CD, Stis AE, Helms AS, Baker BM. Microenvironmental determinants of organized iPSC-cardiomyocyte tissues on synthetic fibrous matrices. Biomaterials science. 2021;9(1):93-107.</p> <p>[5] Jayne RK, Karakan MÇ, Zhang K, Pierce N, Michas C, Bishop DJ, Chen CS, Ekinci KL, White AE. Direct laser writing for cardiac tissue engineering: a microfluidic heart on a chip with integrated transducers. Lab on a Chip. 2021;21(9):1724-37.</p> <p>[6] Karakan MÇ. A Direct-Laser-Written Heart-on-a-Chip Platform for Generation and Stimulation of Engineered Heart Tissues (Doctoral dissertation, Boston University, 2023).</p>
Analysis of division and replication cycles in E. coli using time-lapse microscopy, microfluidics and the MoMA software
<p>Dataset used in the publication "Initiation of chromosome replication controls both division and replication cycles in E. coli through a double-adder mechanism" by Guillaume Witz, Erik van Nimwegen and Thomas Julou (<a href="https://doi.org/10.1101/593590">https://doi.org/10.1101/593590</a>).</p> <p>The zip folder contains four subfolders each containing data corresponding to a given growth condition. Each subfolder contains one folder with images of time-lapses of E. coli cells growing in single microfluidics growth lanes and one folder with data obtained by analysing those images with the software MoMA (<a href="https://github.com/fjug/MoMA">https://github.com/fjug/MoMA</a>).</p>
Time lapse microscopy images of Saccharomyces cerevisiae's full life cycle
Open the record for dataset details and reuse information.
FibroTUG platforms: Time-lapse microscopy dataset of engineered cardiac microbundles
Open the record for dataset details and reuse information.
Engineered cardiac microbundle time-lapse microscopy image dataset
Open the record for dataset details and reuse information.
Strain gauge platforms: Time-lapse microscopy dataset of engineered cardiac microbundles
Open the record for dataset details and reuse information.
Super-resolved Reflectance Confocal Microscopy time-lapse imaging of a living MEF cell lamellipod
<p>This movies presents a time-lapse of a label-free living Mouse embryonic fibroblast cell observed with super-resolved rescanned reflectance confocal microscopy.. </p>
STrack: A tool to Simply Track bacterial cells in microscopy time-lapse images
<p>The datasets consist of time-lapse images underlying the research article "STrack: A tool to Simply Track bacterial cells in microscopy time-lapse images". Please visit the STrack github page for instructions on how to install and use STrack to track cells in images containing segmented cell masks: https://github.com/Helena-todd/STrack</p> <p>The data was generated at the Department of Fundamental Microbiology, University of Lausanne, 1015 Lausanne, Switzerland, by Tania Miguel Trabajo. The datasets are organised in four folders, one per bacterial species (<em>Pseudomonas putida, Pseudomonas veronii, Rahnella and Lysobacter</em>), that each contain 5 time-lapse datasets. Each of the 20 folders is organised in two subfolders, containing:</p> <p>- the raw, phase contrast, timelapse images (taken with a Nikon ECLIPSE Ti Series inverted microscope coupled with a Hamamatsu C11440 22CU camera and a Nikon CFI Plan Apo Lambda 100X Oil objective)</p> <p>- the manually segmented masks (manually generated using the QuPath open-source software for bioimage analysis )</p> <p>Dowload and unzip to view the contents.</p>
Heterogeneous timing of asexual cycles in Plasmodium falciparum quantified by extended time-lapse microscopy
<p>Malarial fever arises from the synchronous bursting of human red blood cells by the <em>Plasmodium</em> parasite. The released parasites re-infect neighboring red blood cells and undergo another asexual cycle of differentiation and proliferation for 48 hours, before again bursting synchronously. The synchrony of bursting is lost during in vitro culturing of the parasite outside the human body, presumably because the asexual cycle is no longer entrained by host-specific circadian cues. Therefore, most in vitro malaria studies have relied on the artificial synchronization of the parasite population. However, much remains unknown about the degree of timing heterogeneity of asexual cycles and how artificial synchronization may affect this timing. Here, we combined time-lapse fluorescence microscopy and long-term culturing to follow single cells and directly measure the heterogeneous timing of in vitro asexual cycles. We first demonstrate that unsynchronized laboratory cultures are not fully asynchronous and the parasites exhibit a bimodal distribution in their first burst times. We then show that synchronized and unsynchronized cultures had similar asexual cycle periods, which indicates that artificial synchronization does not fundamentally perturb asexual cycle dynamics. Last, we demonstrate that sibling parasites descended from the same schizont exhibited significant variation in asexual cycle period, although smaller than the variation between non-siblings. The additional variance between non-siblings likely arises from the variable environments and/or developmental programs experienced in different host cells.</p>
Heterogeneous timing of asexual cycles in Plasmodium falciparum quantified by extended time-lapse microscopy
Open the record for dataset details and reuse information.
Microscopy time-lapse of DNA droplet dispersion by amphiphile-motifs
<p>Time-lapse microscopy data of DNA Y-motifs (color channel 1) and DNA amphiphile-motifs (color channel 2), time step between consecutive time points is 3 minutes. Data were recorded with ambient heating of the microscope enclosure to 40°C. Data were 3D-deconvolved (Richardson-Lucy, 8 iterations), The repository contains the data saved from the microscope software (NIS Elements) as well as the exported .tif data. Sometimes problems occur with import from .nd2 when using the BioFormats importer, in this case it is recommended to instead use the .tiff data. The final figure produced from the raw data is also included as a .png and the source .svg file.</p> <p>Additional image information</p> <p>Objective: Apo LWD 40x WI λS DIC N2</p> <p>Width: 99.9375 microns (615)<br> Height: 99.9375 microns (615)<br> Depth: 12.6 microns (21)<br> Size: 30MB<br> Resolution: 6.1538 pixels per micron<br> Voxel size: 0.1625x0.1625x0.6 micron^3</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.