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26 results for “particle detection”

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zenodo28/100

Figure 1 from: Rosenblad MA, Martín MP, Tedersoo L, Ryberg M, Larsson E, Wurzbacher C, Abarenkov K, Nilsson RH (2016) Detection of signal recognition particle (SRP) RNAs in the nuclear ribosomal internal transcribed spacer 1 (ITS1) of three lineages of ectomycorrhizal fungi (Agaricomycetes, Basidiomycota). MycoKeys 13: 21-33. https://doi.org/10.3897/mycokeys.13.8579

Figure 1 - Schematic illustration of the fungal ITS region and neighboring rDNA genes. The subregions ITS1, 5.8S, and ITS2 of the ITS region are indicated along with the SRP RNA in the first part of the ITS1. The absolute positions of the subregions and the SRP RNA are provided in Suppl. material 2.

opencc-by-4.0May 2016View details →
ClinicalTrials.gov28/100

Pair Production PET Imaging to Detect Particle Distribution in Patients Undergoing Yttrium-90 Radioembolization

ClinicalTrials.gov study NCT02848638. IPD Sharing: NO. Countries: 0. Publications: 1.

closedIPD-NOFeb 2026View details →
dryad28/100

Data from: Automated single particle detection and tracking for large microscopy datasets

Open the record for dataset details and reuse information.

publicApr 2016View details →
ClinicalTrials.gov24/100

Rapid Detection of Pseudomonas Aeruginosa in Bronchoalveolar Lavage Fluid Using Label-free Single-particle Imaging Technology and Assessment of Post-treatment Efficacy in Patients With Pseudomonas Aer

ClinicalTrials.gov study NCT06986512. IPD Sharing: Not stated. Countries: 1. Publications: 0.

restrictedIPD-UNDECIDEDFeb 2026View details →
zenodo16/100

DMP: Production and detection of HIV-Gag particles produced by Saccharomyces cerevisiae

<h2>dataset description</h2> <p>doi: 10.70124/kzk0s-kdq60</p> <p>The following description is used to give a comprehensive overview of the data structure and data management generated in a set of experiments designed to answer the following questions:</p> <ol> <li>can we establish a robust production and purification system for HIV-Gag virus-like particles (VLPs) in the yeast <em>Saccharomyces cerevisiae</em>?</li> <li>can we also show the same results with an already described modified version called Gag:sGFP?</li> </ol> <p><strong>important abbreviations</strong>:</p> <p><strong>Gag</strong> - group-specific antigen, a core structural protein-complex found in some viruses in different variants.</p> <p><strong>sGFP</strong> - superfolder green fluorescent protein, a common reporter used in biochemical and microbiological experiments which matures quickly after expression and is suitable for strong overexpression systems.</p> <p><strong>HIV</strong> - human immunodeficiency virus, an immune system compromising virus specific to humans.</p> <p><strong>v</strong>irus-<strong>l</strong>ike <strong>p</strong>article - also called <strong>VLP</strong>; a non-infectious particle that resembles a mature virus but lacks key features like the ability to self-reproducet or other virulent factors. In the case of the HIV-Gag it mainly consist of the Gag protein, which self-assembles at the host cell wall and is released as a spherical structure.</p> <p>The data in this dataset is generated, collected, and analyzed by Adrian K&ouml;ber.</p> <h3>Context and methodology</h3> <ul> <li>This project mainly involves methods from the fields of biochemistry and microbiology. It includes SDS-PAGE, Western Blotting, and fluorescence in 96-well format, and general cultivation methods for yeast.</li> <li>This dataset serves the main purpose of showing the robustness of the laboratory procedure which is used to generate and purify the VLPs, which is built on two main publications.</li> <li>This dataset was created as a part of my Ph.D. thesis project and resolves around a center point of the underlying laboratory procedures.</li> </ul> <h3>Technical details</h3> <ul> <li>The general structure of the dataset will include the raw data from fluorescence measurements in .csv format with appropriate sample tags to identify the samples, possible dilutions, used volumes, or other relevant information. Pictures are saved as .tiff in an unaltered version. There will be descriptive metadata or README files for each dataset and a general README file for the overall process description, which also includes a detailed protocol for the method with the aim of providing an in-depth manual to redo the experiments themselves.</li> <li>The analyzed and annotated data will also be provided in a .csv or .tiff format appropriate to the data structure; e.g. tabular data -&gt; .csv</li> <li>The dataset will include a three-layered folder structure with a main folder containing the sub-folders for the raw and analyzed data, which in turn include folders for the different experiment parts. The naming convention is described in the appended metadata file, in short: main folder: experiment ID, sub-folder: experiment IDraw/anaylzed, internal folder: experiment ID_raw_date.</li> <li>The aim is to have no proprietary software needed to open or evaluate the data itself. Data will be processed in Excel, Powerpoint, or Texteditor to the stated level of detail and then converted to a non-proprietary file format (.csv; .tiff; .xml; .rtf)</li> <li>There will be also proprietary data formats like .xlsx and .scn, which can be used, if possible.</li> <li>The dataset includes a general metadata description/documentation in .rtf format which will include the necessary details for the procedure, data analysis, and data provenance.</li> </ul> <h3>Further details</h3> <ul> <li>To re-do the experiments it will be necessary to have access to the correct <em>S. cerevisiae</em> strains, which are owned by the group of Matthias Steiger (TU Wien, E166-5-2) and are located in the BH building of the Campus Getreidemarkt at the Gumpendorfer Stra&szlig;e 1A, 1060 Wien, Austria. For that please contact adrian.koeber@tuwien.ac.at or matthias.steiger@tuwien.ac.at</li> <li>The genetic construct maps will also be provided in an open-source format with annotations to discern the crucial genetic components.</li> <li>If there are questions concerning the re-use of the data please contact adrian.koeber@tuwien.ac.at or matthias.steiger@tuwien.ac.at.</li> </ul>

restrictedcc-by-4.0Dec 2023View details →
zenodo12/100

Detection results of NMC particles in composite battery cathodes

<p>This dataset shows more examples of the NMC particles detection overlayed with the original images in composite battery cathodes.</p> <pre><code>@journal{li2022networkevolution, title={Dynamics of particle network in composite battery cathodes}, author={Li, Jizhou and Sharma, Nikhil and Jiang, Zhisen and Yang, Yang and Monaco, Federico and Xu, Zhengrui and Hou, Dong and Ratner, Daniel and Pianetta, Piero and Cloetens, Peter and Lin, Feng and Zhao, Kejie and Liu, Yijin}, year={2022}, journal={Science} }</code></pre>

restrictedApr 2022View details →

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Allen Brain Atlas

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neuroscienceopenDocumentation, web resources, and API references are available online.
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behavioral-neuroscienceopenThe DataShare record exposes download links for annotations, documentation, license text, and the zipped per-snippet data directory.
Last verified 2026-04-30Open record

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.

dandi-nwb
electrophysiologyopenPublished Dandiset metadata and archive endpoints are available through the production DANDI API.
Last verified 2026-04-30Open record

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.

ibl
behavioral-neuroscienceopenPublic sessions can be searched and loaded from the IBL public data server through ONE.
Last verified 2026-04-29Open record

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.

openneuro
neuroscienceopenPublished datasets are available on demand over the internet.
Last verified 2026-04-29Open record