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111,247 results for “cells”
Wings: 68, Loew system for wing cells (Mydas lividus Curran); 69, Comstock Needham system for wing veins tNernomouiae pantherinus Gerstaecker); 70, Apiophora paulseni Philippi, a: open 2nd submarginal cell; b: reduced size of axillary lobe; 71., Mitrodetus sp.; 72 Pseudonomoneura sp. in The American Genera of Mydidae (Diptera), with the Description of three new Genera and two new Species
Wings: 68, Loew system for wing cells (Mydas lividus Curran); 69, Comstock Needham system for wing veins tNernomouiae pantherinus Gerstaecker); 70, Apiophora paulseni Philippi, a: open 2nd submarginal cell; b: reduced size of axillary lobe; 71., Mitrodetus sp.; 72 Pseudonomoneura sp.
Colony Formation Dataset of Simulated Cell Cultures
<p>This is a dataset of synthetic cell colony formation generated by an off-lattice individual-based model. The calculated shape features of the artificial cell aggregates can be related to the parameter values of the simulated agents.</p>
HDAC11 target engagement assay development in cells - CETSA
<p><strong>Methods</strong></p> <p><strong>Permeabilized CETSA</strong></p> <p>HEK293T cells were seeded in 6-well plates (8 x 10<sup>5</sup> cells/well) in DMEM supplemented with 10% FBS , penicillin (100 U/mL) and streptomycin (100 µg/mL). 4 h after seeding cells were transfected with 0.2 µg of N-terminally NanoLuc-tagged HDAC11 and 1.8 µg of empty pcDNA3.1 vectors using X-tremeGENE™ HP transfection reagent, following manufacturer instructions. Next day cells were harvested using Trypsin-EDTA, and resuspended in pre-warmed Opti-MEM (no phenol-red) at a concentration of 1.2 x 10<sup>5</sup> cells/ml. A 10x stock solution of digitonin (500 µg/ml, Sigma) and 100x stock solution of protease inhibitor cocktail (cOmplete™, Mini, EDTA-free,<em> </em>Sigma<em>)</em> was prepared in Opti-MEM and DMSO, respectively. The protease inhibitor / DMSO stock solution was used as vehicle to prepare 100x stock solutions of all test compounds. The 10x digitonin stock solution and 100x test compound / vehicle stock solution were pre-dispensed into 96-well PCR reaction plates at 10 µl/well and 1 µl/well, respectively. Next, 89 µl/well of the cell suspension was added to the pre-loaded PCR plates. Plates were then covered with adhesive plate sealing tape and were incubated at 37°C for 1 h. Immediately prior to heating the PCR plates, a 5x substrate stock solution was prepared by diluting NanoBRET NanoGlo Substrate (Promega) 1:100 into Opti-MEM. The thermal cycler was allowed to reach the designated temperature prior to placement of the PCR plate into the heating block. For Tm determination experiments, duplicate plates containing a fixed concentration of test compounds (30 µM) as well as vehicle control were prepared to perform a 11 point temperature gradient spanning 37-68.5°C for 3 minutes. The plates were allowed to cool at room temperature for 3 minutes after the heat treatment followed by addition of 25 µl 5x substrate stock solution per well. To measure NanoLuc activity 100 µl of sample were transferred from the PCR plate to a white 96-well plate. Total luminescence was measured immediately after substrate addition with CLARIOstar microplate reader (BMG Labtech).</p> <p><strong>Non-permeabilized CETSA</strong></p> <p>HEK293T cells were seeded in 6 well plates (8 x 10<sup>5</sup> cells/well) in DMEM supplemented with 10% FBS , penicillin (100 U/mL) and streptomycin (100 µg/mL). 4 h after seeding cells were transfected with 0.2 µg of N-terminally NanoLuc tagged HDAC11 and 1.8 µg of empty pcDNA3.1 vectors using X-tremeGENE™ HP transfection reagent, following manufacturer instructions. Next day cells were tretaed with compounds/DMSO for 6 h. Cells were harvested using Trypsin-EDTA and resuspended in pre-warmed Opti-MEM (no phenol-red) at a concentration of 1 x 10<sup>5</sup> cells/ml. Next, 100 µl/well of the cell suspension was added to the pre-loaded PCR plates. Immediately prior to heating the PCR plates, a 5x substrate stock solution was prepared by diluting NanoBRET NanoGlo Substrate (Promega) 1:100 into Opti-MEM. The thermal cycler was allowed to reach the designated temperature prior to placement of the PCR plate into the heating block. For Tm determination experiments, duplicate plates containing a fixed concentration of test compounds (30 µM) as well as vehicle control were prepared to perform a 11 point temperature gradient spanning 37-72°C for 3 minutes. The plates were allowed to cool at room temperature for 3 minutes after the heat treatment followed by addition of 25 µl 5x substrate stock solution per well. To measure NanoLuc activity 100 µl of sample were transferred from the PCR plate to a white 96-well plate. Total luminescence was measured immediately after substrate addition with CLARIOstar microplate reader (BMG Labtech).</p> <p> </p>
Megakaryocyte volume modulates bone marrow niche properties and cell migration dynamics
<p>Supplementary videos showing raw time and z-stacks as well a final, processed result for Neutrophil tracking in naive and platelet depleted mouse.</p> <p>Matlab scripts to run simulation of megakaryocytes, neutrophils and hematopoetic stem cell in a vessel environment.</p> <p>Ilastik training data set used in segmentation of bone and bone marrow.</p> <p> </p>
Dataset and Data treatment for Data mining Raman Microspectroscopic Responses of Cells to Drugs in Vitro using Multivariate Curve Resolution-Alternating Least Squares
<p><strong>Matlab scripts for the simulation and treatment of Raman datasets obtained from time dependent experiments Using MCR-ALS.</strong></p> <p> </p> <p><strong>- SIMULATED DATA: </strong>Simulated data is obtained by adding spectra of artificially generated responses (weighted considering artificially generated time profiles) to an experimental cell spectrum (Initial component) Three Different Scenarios are generated. </p> <p>Spectral and time profiles are obtained from here: </p> <p> </p> <p><strong>- EXPERIMENTAL DATA: </strong>DOX dataset obtained from here</p> <p>https://doi.org/10.1002/jbio.201800328</p> <p> </p> <p> </p> <p><strong>- DATA ANALYSIS INSTRUCTIONS</strong></p> <p>Run <em>datatreatment.m</em></p>
Supplementary data for: Detection of expressed mutations in acute myeloid leukemia cells using single cell RNA-sequencing
<p>Supplemental data for the publication:<br> Detection of expressed mutations in acute myeloid leukemia cells using single cell RNA-sequencing </p> <p>Contents: <br> - expression_matrices.tar - Gene/Barcode expression matrices from `cellranger count`<br> - *.seurat.rds - R object files with Seurat analyses and data structures for each sample<br> - scrna_mutations.tar.gz - copy of a git repository containing additional scripts and data - also hosted at <a href="https://github.com/genome/scrna_mutations">https://github.com/genome/scrna_mutations</a> (snapshot as of May 20, 2019)</p>
Inferelator Saccharomyces Cerevisiae Single-Cell Data Set
<p>This data is associated with the Inferelator package. It has an expression data set (103118_SS_Data.tsv.gz), which is a [Cells x Genes] TSV file which has 5 included metadata columns [Genotype, Genotype_Group, Replicate, Condition, tenXBarcode]. It also contains a prior data matrix generated from the YEASTRACT database (YEASTRACT_Both_20181118.tsv), a gold standard derived from the YEASTRACT database (gold_standard.tsv), a list of transcription factors (tf_names_restrict.tsv), and a list of protein-coding genes (orfs.tsv). It was initially used in Jackson, C.A., Castro, D.M., Saldi, G.-A., Bonneau, R., and Gresham, D. (2019). Gene regulatory network reconstruction using single-cell RNA sequencing of barcoded genotypes in diverse environments. BioRxiv 581678.</p>
A comparison of automatic cell identification methods for single-cell RNA-sequencing data
<p>Benchmark datasets used to evaluate the performance of 22 classifiers for cell type classification for scRNA-seq data</p>
sirselim/immunecell_methylation_paper_data: First release of data for immune cell epigenetics (methylation) manuscript
<p>This is the first release of the data to be made public and accessible with the manuscript.</p>
Processed Hi-C contact matrices for "Single-cell DNA replication profiling identifies spatiotemporal developmental dynamics of chromosome organization"
<p>Processed Hi-C interaction matrices (iterative correction) saved in .hic format (40kb bins).</p> <p>.hic files were generated by juicer pipeline using processed Hi-C interaction matrices.</p> <p>Only <em>cis </em>interactions were available.</p> <p>To extract the data, please see </p> <p>https://github.com/aidenlab/juicer/wiki/Data-Extraction</p>
A Galaxy-based training resource for single-cell RNA-seq quality control and analyses
<p>This is the tutorial data for the 'Single-cell quality control with scater' tutorial on the Galaxy Training Network. The data is the same dataset that is used as the inbuilt example dataset within scater, but has been implemented as individual files.</p>
Processed data for "Dissociation of solid tumour tissues with cold active protease for single-cell RNA-seq minimizes conserved collagenase-associated stress responses"
<p>tar.gz of processed data in the form of compressed R files (rds) of SingleCellExperiment (<a href="https://bioconductor.org/packages/release/bioc/html/SingleCellExperiment.html">https://bioconductor.org/packages/release/bioc/html/SingleCellExperiment.html</a>) objects and a metadata csv for the data in the publication <em>Dissociation of solid tumour tissues with cold active protease for single-cell RNA-seq minimizes conserved collagenase-associated stress responses </em>(O'Flanagan et al. 2019).</p>
Steady states using PARADIGM for 8 cell lines from CCLE
<p>This dataset has the input data + result dataset (steady states per cell line) that was the product of using the CLSS rbbt workflow (that uses the PARADIGM tool) for 8 cell lines from CCLE. A CASCADE-derived pathway file was used as input for PARADIGM.</p>
Extention to the TNBC dataset, brain section and cell type
<p>This dataset is partly an extension of the TNBC dataset that can be found in the following link: https://zenodo.org/record/1175282#.Ws2n_vkdhfA</p> <p>In particular, we give the cellular type annotations of each annotated cell.<br> In addition to the TNBC, we added 18 annotated images of brain section downloaded from the TCGA.<br> This is still officially unpublished and has been submitted.<br> Currently, if you use this dataset please our paper "Scale dependant layer for self-supervised nuclei encoding" by Peter Naylor, Yao-Hung Hubert Tsai, Marick Laé and Makoto Yamada.</p>
Fig. 9. T. thermophila cells immunostained with monoclonal anti-cdc14A in Effects of Roscovitine on Schedule of Divisional Morphogenesis, Basal Bodies Proliferation and Cell Divisions in Tetrahymena thermophila
Fig. 9. T. thermophila cells immunostained with monoclonal anti-cdc14A antibody. Cs and nCS – apical couplets of basal bodies for proter and opisthe, respectively; Ma – macronucleus. Other explanations as in Figs 1 and 8. Bar: 10 µm, bar in D for B–D.
Fig. 7. T. thermophila cells immunostained with the antiserum against component B in Effects of Roscovitine on Schedule of Divisional Morphogenesis, Basal Bodies Proliferation and Cell Divisions in Tetrahymena thermophila
Fig. 7. T. thermophila cells immunostained with the antiserum against component B of epiplasm. DF – staining around the deep fibers. Other explanations as in Fig. 1. Bar: 10 µm.
Fig. 2 in Effects of Roscovitine on Schedule of Divisional Morphogenesis, Basal Bodies Proliferation and Cell Divisions in Tetrahymena thermophila
Fig. 2. Localization of nuclei in control and roscovitine treated T. tetrmophila. The cells were immunostained with the anti-centrin 20H5 antibody and stained with DAPI. A and B – control cells in the VI stage of morphogenesis, and early cytokinesis, respectively; C and D – roscovitine treated cells (4 h) in the VI stage of morphogenesis and in cytokinesis respectively. Arrows – micronuclei (in the C micronucleus in opisthe is out of focus). Bar: 10 µm.
Fig. 4. Postdivider cells after 5.5 h in Effects of Roscovitine on Schedule of Divisional Morphogenesis, Basal Bodies Proliferation and Cell Divisions in Tetrahymena thermophila
Fig. 4. Postdivider cells after 5.5 h of roscovitine treatment. Cells were immunostained with anti-centrin 20H5 antibody. A and A' – ventral and dorsal views of the same proter cell with remnants of the OA2; B–C opisthe cells, B – opisthe with ARF on dorsal side, C – opisthe with remnants of oral structures; D and D' – ventral and dorsal views of the same cell; E and E' – ventral and dorsal views of the same opisthe during pinching off the OA. Other explanations as in Fig. 1. Bar: 10 µm for A–E'.
Fig. 5 in Effects of Roscovitine on Schedule of Divisional Morphogenesis, Basal Bodies Proliferation and Cell Divisions in Tetrahymena thermophila
Fig. 5. Mean cell sizes, positions of OA1, OA2 and fission zone in control and in roscovitine treated cells. Upper panel: early and late control dividers, lower panel: early dividers after 3.5 h roscovitine treatment, late dividers after 3.5 and 5.5 h roscovitine treatment. The shape of cells is represented by elipses. Solid horizontal lines – cells "equator", dotted horizontal lines – positions of the fission furrow. All sizes and distances were drawn to the same scale. Bar: 10 µm. The measurements represent means of at least 10 specimens for each cell sample.
Fig. 6 in Effects of Roscovitine on Schedule of Divisional Morphogenesis, Basal Bodies Proliferation and Cell Divisions in Tetrahymena thermophila
Fig. 6. Correlation of length of proters and shift of the fission zone in relation to OA2 induced by roscovitine in late dividers. The shift of the fission zone was measured as a difference between length of the proters and distance from cell apex to the anterior end of the OA2 (ordinate). Each point in this diagram represent individual cell. Open symbols – untreated cells, close symbols – cells treated with roscovitine for 3.5 and 5.5 h (pooled).
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.