Example Microscopy Metadata JSON files produced using Micro-Meta App to document example microscopy experiments performed at individual core facilities
Notice bibliographique
Résumé
Example Microscopy Metadata (Microscope.JSON and Settings.JSON) files produced using Micro-Meta App to document the Hardware Specifications of example Microscopes and the Image Acquisition Settings utilized to acquire example images as listed in the table below. For each facility, the dataset contains two JSON files: Microscope.JSON file (e.g., 01_marcello_uliverpool_cci_zeiss_axioobserz1_lsm710.json) Settings.JSON file (indicated with the name of the image and with the _AS suffix) Micro-Meta App was developed as part of a global community initiative including the 4D Nucleome (4DN) Imaging Working Group, BioImaging North America (BINA) Quality Control and Data Management Working Group, and QUAlity and REProducibility for Instrument and Images in Light Microscopy (QUAREP-LiMi), to extend the Open Microscopy Environment (OME) data model. The works of this global community effort resulted in multiple publications featured on a recent Nature Methods FOCUS ISSUE dedicated to Reporting and reproducibility in microscopy. Learn More! For a thorough description of Micro-Meta App consult our recent Nature Methods and BioRxiv.org publications! Nr. Manufacturer Model Tier Εxperiment Type Facility Name Department and Institution URL References 1 Carl Zeiss Microscopy Axio Observer Z1 (with LSM 710 scan head) 1 3D visualization of superhydrophobic polymer-nanoparticles Centre for Cell Imaging (CCI) University of Liverpool https://cci.liv.ac.uk/equipment_710.html Upton et al., 2020 2 Carl Zeiss Microscopy Axio Observer (Axiovert 200M) 2 Μeasurement of illumination stability on Chinese Hamster Ovary cells expressing Paxillin-EGFP Advanced BioImaging Facility (ABIF). McGill University https://www.mcgill.ca/abif/equipment/axiovert-1 Kiepas et al., 2020 3 Carl Zeiss Microscopy Axio Observer Z1 (with Spinning Disk) 2 Immunofluorescence imaging of cryosection of Mouse kidney Imagerie Cellulaire; Quality Control managed by Miacellavie (https://miacellavie.com/) Centre de recherche du Centre Hospitalier Université de Montréal (CR CHUM), University of Montreal https://www.chumontreal.qc.ca/crchum/plateformes-et-services (the web site is for all core facilities, not specifically for the core facility hosting this microscope) Pilliod et al., 2020 4 Carl Zeiss Microscopy Axio Imager Z2 (with Apotome) 2 Immunofluorescence imaging of mitotic division in Hela cells using Bioimaging Unit Newcastle University https://www.ncl.ac.uk/bioimaging/ Watson et al., 2020 5 Carl Zeiss Microscopy Axio Observer Z1 2 Fluorescence microscopy of human skin fibroblasts from Glycogen Storage Disease patients. Life Imaging Center (LIC) Centre for Integrative Signalling Analysis (CISA), University of Freiburg https://miap.eu/equipments/sd-i-abl/ Hannibal et al., 2020 6 Leica Microsystems DMI6000B 2 3D immunofluorescence imaging rhinovirus infected macrophages IMAG'IC Confocal Microscopy Facility Institut Cochin, CNRS, INSERM, Université de Paris https://www.institutcochin.fr/core_facilities/confocal-microscopy/cochin-imaging-photonic-microscopy/organigram_team/10054/view Jubrail et al., 2020 7 Leica Microsystems DM5500B 2 Immunofluorescence analysis of the colocalization of PML bodies with DNA double-strand breaks Bioimaging Unit Edwardson Building on the Campus for Ageing and Vitality, Newcastle University https://www.ncl.ac.uk/bioimaging/equipment/leica-dm5500/#overview da Silva et al., 2019; Nelson et al., 2012 8 Leica Microsystems DMI8-CS (with TCS SP8 STED 3X) 2 Live-cell imaging of N. benthamiana leaves cells-derived protoplasts Center for Advanced Imaging (CAi) School of Mathematics/Natural Sciences, Heinrich-Heine-Universität Düsseldorf https://www.cai.hhu.de/en/equipment/super-resolution-microscopy/leica-tcs-sp8-sted-3x Singer et al., 2017; Hänsch et al., 2020 9 Nikon Instruments Eclipse Ti 2 Immunofluorescence analysis of the cytoskeleton structure in COS cells Advanced Imaging Center (AIC) Janelia Research Campus, Howard Hughes Medical Institute https://www.janelia.org/support-team/light-microscopy/equipment Abdelfattah et al., 2019; Qian et al., 2019; Grimm et al., 2020 10 Nikon Instruments Eclipse Ti-E (HCA) 2 Τime-lapse analysis of the bursting behavior of amine-functionalized vesicular assemblies Light Microscopy Facility (IALS-LIF) Institute for Applied Life Sciences, University of Massachusetts at Amherst https://www.umass.edu/ials/light-microscopy Fernandez et al., 2020 11 Nikon Instruments/Coleman laboratory (customized) TIRF HILO Epifluorescence light Microscope (THEM)/ Eclipse Ti 2 Single-particle tracking of Halo-tagged PCNA in Lox cells Coleman laboratory Anatomy and Structural Biology Department, The Albert Einstein College of Medicine https://einsteinmed.org/faculty/12252/robert-coleman/ Drosopoulos et al., 2020 12 Nikon Instruments Eclipse Ti (with Andor Dragon Fly Spinning Disk) 2 Investigation of the 3D structure of cerebral organoids Montpellier Resources Imagerie Centre de Recherche de Biologie cellulaire de Montpellier (MRI-CRBM), CNRS, Univerity of Montpellier https://www.mri.cnrs.fr/en/optical-imaging/our-facilities/mri-crbm.html Ayala-Nunez et al., 2019 13 Nikon Instruments Eclipse Ti2 2 Ιmmunofluorescence imaging of cryosections of mouse hearth myocardium Neuroscience Center Microscopy Core Neuroscience Center, University of North Carolina https://www.med.unc.edu/neuroscience/core-facilities/neuro-microscopy/ Aghajanian et al., 2021 14 Nikon Instruments Eclipse Ti2 2 Live-cell imaging of bacterial cells expressing GFP-PopZ Microscopy Resources on the North Quad (MicRoN) Harvard Medical School https://micron.hms.harvard.edu/ Lim and Bernhardt 2019; Lim et al., 2019 15 Olympus/Biomedical Imaging Group (customized) TIRF Epifluorescence Structured light Microscope (TESM)/IX71 3 3D distribution of HIV-1 in the nucleus of human cells Biomedical Imaging Group Program in Molecular Medicine, University of Massachusetts Medical School https://trello.com/b/BQ8zCcQC/tirf-epi-fluorescence-structured-light-microscope Navaroli et al., 2012 16 Olympus/Computer Vision Laboratory (customized) 3D BrightField Scanner/IX71 3 Transmitted light brightfield visualization of swimming spermatocytes Laboratorio Nacional de Microscopia Avanzada (LNMA) and Computer Vision Laboratory of the Institute of Biotechnology Universidad Nacional Autonoma de Mexico (UNAM) https://lnma.unam.mx/wp/ Pimentel et al., 2012; Silva-Villalobos et al., 2014 Getting started Use these videos to get started with using Micro-Meta App after installation into OMERO and downloading the example data files: Video 1 Video 2 More information For full information on how to use Micro-Meta App please utilize the following resources: Micro-Meta App website Full documentation Installation instructions Step-by-Step Instructions Tutorial Videos Background If you want to learn more about the importance of metadata and quality control to ensure full reproducibility, quality and scientific value in light microscopy, please take a look at our recent publications describing the development of community-driven light 4DN-BINA-OME Microscopy Metadata specifications Nature Methods and BioRxiv.org and our overview manuscript entitled A perspective on Microscopy Metadata: data provenance and quality control.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,005 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,002 |
| Bibliométrie | 0,004 | 0,005 |
| Études des sciences et des technologies | 0,002 | 0,000 |
| Communication savante | 0,003 | 0,004 |
| Science ouverte | 0,003 | 0,003 |
| Intégrité de la recherche | 0,002 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,244 | 0,198 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».