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278
datasets available to search
ShareScore release 0.9.0
Dataset results
278 results for “cytometry”
Discrete Flow Cytometry of Underway Samples from TN413 Using a BD Influx Cell Sorter
<p>The dataset consists of BD Influx-based analysis of phytoplankton populations from discrete flow cytometry data collected underway during the University of Washington School of Oceanography 2023 undergraduate senior thesis cruise (TN413) oceanographic research cruise from Hawaii to Fiji. The data consists of cell abundance, cell size (equivalent spherical diameter), carbon quota, and carbon biomass for picophytoplankton populations, namely the cyanobacteria Prochlorococcus and Synechococcus, and small eukaryotic phytoplankton (<5 μm ESD). Time is in UTC format, latitude and longitude are in decimal degrees, and depth is in meters. Further information can be found here: https://github.com/fribalet/FCSplankton</p>
Study of Platelets Sialylation by Flow Cytometry for the Differential Diagnosis of ICT
ClinicalTrials.gov study NCT03421392. IPD Sharing: NO. Countries: 1. Publications: 2.
DNA Cytometry for Cervical Cancer Screening in China
ClinicalTrials.gov study NCT00902551. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Neutrophil Biomarker Test for Predicting Clinical Benefit From Immunotherapy Based on Flow Cytometry Analysis
ClinicalTrials.gov study NCT07246759. IPD Sharing: UNDECIDED. Countries: 3. Publications: 8.
Flow Cytometry Applied to the Diagnosis of Peri-anaesthesic Reactions
ClinicalTrials.gov study NCT01305161. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Identification of B Regulatory Cells by Flow Cytometry
ClinicalTrials.gov study NCT06876506. IPD Sharing: NO. Countries: 1. Publications: 3.
Diagnostic Accuracy of Urine Flow Cytometry in Excluding Bacteruria
ClinicalTrials.gov study NCT04686292. IPD Sharing: NO. Countries: 1. Publications: 3.
Interest of Flow Cytometry for the Diagnosis, the Follow up and Specific Immunotherapy (SIT) Arrest of Hymenoptera Venom Allergy
ClinicalTrials.gov study NCT00805402. IPD Sharing: Not stated. Countries: 1. Publications: 1.
A Study On The Prediction of Neoadjuvant Efficacy For Rectal Cancer Based On MR Cytometry Imaging and Deep-radiomics
ClinicalTrials.gov study NCT07107815. IPD Sharing: Not stated. Countries: 1. Publications: 1.
STAT4 in Multiple Sclerosis by PCR and Flow Cytometry
ClinicalTrials.gov study NCT03893344. IPD Sharing: Not stated. Countries: 1. Publications: 2.
Imaging mass cytometry data from IDH wildtype glioblastomas
Open the record for dataset details and reuse information.
Data from: Flow cytometry combined with viSNE for analysis of microbial biofilms and detection of microplastics
Open the record for dataset details and reuse information.
Hematopathologist-annotated mass cytometry dataset of acute myeloid leukemia diagnostic specimens
Open the record for dataset details and reuse information.
Data from: The ORFIUS complex regulates ORC2 localization at replication origins (Flow cytometry)
Open the record for dataset details and reuse information.
Picophytoplankton and bacteria abundances analyzed with flow cytometry (FCM) from CCE LTER process cruises the California Current region, 2006 - 2017.
Picophytoplankton populations and non-pigmented prokaryotes are sampled within the California Current Ecosystem (CCE) for abundances at various depths. Seawater is collected from Niskin bottles and cells are fixed in the field aboard the process cruises (since 2006, ongoing) with paraformaldehyde, and stained with a DNA-specific dye back in the laboratory. The cells are enumerated by an Altra flow cytometer (with a syringe pump for volumetric sample delivery) simultaniously with argon ion lasers, to distinguish three major populations of photoautotrophs (Prochlorococcus, Synechococcus, and pico-eukaryotes) and the assemblage of heterotrophic prokaryotes collectively referred to as H-Bact.
Picophytoplankton and bacteria total carbon estimates from cell counts analyzed with flow cytometry (FCM) from CCE LTER process cruises in the California Current region, 2006 - 2017.
Picophytoplankton populations and non-pigmented prokaryotes are sampled within the California Current Ecosystem (CCE) for abundances from various depths. Seawater is collected from Niskin bottles and cells are fixed in the field aboard the survey cruises (since 2004, ongoing) with paraformaldehyde, and stained with a DNA-specific dye back in the laboratory. The cells are enumerated by an Altra flow cytometer (with a syringe pump for volumetric sample delivery) simultaniously with argon ion lasers, to distinguish three major populations of photoautotrophs (Prochlorococcus, Synechococcus, and pico-eukaryotes) and the assemblage of heterotrophic prokaryotes collectively referred to as H-Bact. FCM abundance estimates for each are converted to carbon biomass equivalents using mixed-layer estimates.
Link to dataset related to article "Development, application and computational analysis of high-dimensional fluorescent antibody panels for single-cell flow cytometry"
<p>The interrogation of single cells is revolutionizing biology, especially our understanding of the immune system. Flow cytometry is still one of the most versatile and high-throughput approaches for single-cell analysis, and its capability has been recently extended to detect up to 28 colors, thus approaching the utility of cytometry by time of flight (CyTOF). However, flow cytometry suffers from autofluorescence and spreading error (SE) generated by errors in the measurement of photons mainly at red and far-red wavelengths, which limit barcoding and the detection of dim markers. Consequently, development of 28-color fluorescent antibody panels for flow cytometry is laborious and time consuming. Here, we describe the steps that are required to successfully achieve 28-color measurement capability. To do this, we provide a reference map of the fluorescence spreading errors in the 28-color space to simplify panel design and predict the success of fluorescent antibody combinations. Finally, we provide detailed instructions for the computational analysis of such complex data by existing, popular algorithms (PhenoGraph and FlowSOM). We exemplify our approach by designing a high-dimensional panel to characterize the immune system, but we anticipate that our approach can be used to design any high-dimensional flow cytometry panel of choice. The full protocol takes a few days to complete, depending on the time spent on panel design and data analysis.</p> <p> </p> <p> </p> <p>link related to dataset: https://flowrepository.org/id/FR-FCM-ZYV3</p>
Clustering and kernel density estimation for assessment of measurable residual disease by flow cytometry
<p>Flow cytometry raw data and supplementary table S1.</p>
Data from: Bacterial characterization of Beijing drinking water by flow cytometry and MiSeq sequencing of the 16S rRNA gene
Flow cytometry (FCM) and 16S rRNA gene sequencing data are commonly used to monitor and characterize microbial differences in drinking water distribution systems. In this study, to assess microbial differences in drinking water distribution systems, 12 water samples from different sources water (groundwater, GW; surface water, SW) were analyzed by FCM, heterotrophic plate count (HPC), and 16S rRNA gene sequencing. FCM intact cell concentrations varied from 2.2 × 103 cells/mL to 1.6 × 104 cells/mL in the network. Characteristics of each water sample were also observed by FCM fluorescence fingerprint analysis. 16S rRNA gene sequencing showed that Proteobacteria (76.9–42.3%) or Cyanobacteria (42.0–3.1%) was most abundant among samples. Proteobacteria were abundant in samples containing chlorine, indicating resistance to disinfection. Interestingly, Mycobacterium, Corynebacterium, and Pseudomonas, were detected in drinking water distribution systems. There was no evidence that these microorganisms represented a health concern through water consumption by the general population. However, they provided a health risk for special crowd, such as the elderly or infants, patients with burns and immune-compromised people exposed by drinking. The combined use of FCM to detect total bacteria concentrations and sequencing to determine the relative abundance of pathogenic bacteria resulted in the quantitative evaluation of drinking water distribution systems. Knowledge regarding the concentration of opportunistic pathogenic bacteria will be particularly useful for epidemiological studies.
OMAP-8: Multiplexed Antibody-Based Imaging of Placenta with Imaging Mass Cytometry (IMC), v1.0
<p>OMAP-8 was designed for Imaging Mass Cytometry (IMC) (<a href="https://pubmed.ncbi.nlm.nih.gov/24584193/">https://pubmed.ncbi.nlm.nih.gov/24584193/</a>) of formalin-fixed paraffin-embedded (FFPE) human term-placenta samples. The tissue slides were prepared with a two-step antigen retrieval process (pH 6 and pH 9, as described <a href="https://dx.doi.org/10.17504/protocols.io.bpwumpew">https://dx.doi.org/10.17504/protocols.io.bpwumpew</a>). OMAP antibodies validated by immunohistochemistry and IMC were conjugated to polymers containing metal isotopes. Conjugated antibodies were used to stain processed human term-placenta tissue simultaneously. Regions of the processed tissue were then acquired on the imaging mass cytometer (Hyperion; Standard BioTools) by laser ablation and visualized. The panel contains 26 antibodies conjugated to unique metal isotopes and iridium marks the DNA. This OMAP provides a spatial context for key placenta cell types in the <a href="https://doi.org/10.48539/HBM446.WGLG.755">ASCT+B v.1.0 table</a>. Single-cell RNA sequencing data were used to guide marker selection for multiplexed tissue imaging. For example, ASCL2, HLA-G, PD-L1, CD68 and LYVE1 allow functionally specialized cell types to be visualized and quantified in the placenta. Note that one of our core antibodies is to LYVE1 but, unlike in other tissues where it is used to mark lymphatic vasculature, here we use it to mark the macrophage of the placenta (Hofbauer cells) – there should be no lymphatics in the placenta.</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.