Open Microscopy Environment eXtensible Markup Language
How to cite this record: FAIRsharing.org: OME-XML; Open Microscopy Environment eXtensible Markup Language; DOI: https://doi.org/10.25504/FAIRsharing.zk8p4g; Last edited: March 15, 2018, 11:54 a.m.; Last accessed: Mar 18 2018 7:18 p.m.
Created in 2005
Scope and data types
No XSD schemas defined
Conditions of UseApplies to: Data use
- Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported (CC BY-NC-SA 3.0)
- Creative Commons Attribution 4.0 International (CC BY 4.0)
Metadata matters: access to image data in the real world
Linkert M,Rueden CT,Allan C,Burel JM,Moore W,Patterson A,Loranger B,Moore J,Neves C,Macdonald D,Tarkowska A,Sticco C,Hill E,Rossner M,Eliceiri KW,Swedlow JR
J Cell Biol 2010
No guidelines defined
No semantic standards defined
Models and Formats
OMERO is client-server software for visualization, management and analysis of biological microscope images.
Image Data Resource
IDR is a prototype platform for publishing, mining and integrating bioimaging data at scale, following the Euro-BioImaging/ELIXIR imaging strategy using the OMERO and Bio-Formats open source software built by the Open Microscopy Environment. Deployed on an OpenStack cloud running on the EMBL-EBI’s Embassy resource, it includes image data linked to independent studies from genetic, RNAi, chemical, localisation and geographic high content screens, super-resolution microscopy, and digital pathology.
SSBD: Systems Science of Biological Dynamics
SSBD is a database that collects and shares quantitative biological dynamics data, microscopy images, and software tools. SSBD provides a rich set of resources for analyzing quantitative biological data, such as single-molecule, cell, and gene expression nuclei. Quantitative biological data are collected from a variety of species, sources and methods. These include data obtained from both experiment and computational simulation.
Microenvironment Perturbagen LINCS Center image server
The MEP LINCS project contributes to the development of the NIH Library of Integrated Network-based Cellular Signatures (LINCS) program by developing a dataset and computational strategy to elucidate how microenvironment (ME) signals affect cell intrinsic intracellular transcriptional- and protein-defined molecular networks to generate experimentally observable cellular phenotypes measured by high-content imaging.
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