FAIR High Content Screening in Bioimaging

Scientific Data, vol. 10, pp. 462

Abstract

The Minimum Information for High Content Screening Microscopy Experiments (MIHCSME) is a metadata model and reusable tabular template for sharing and integrating high content imaging data. It has been developed by combining the ISA (Investigations, Studies, Assays) metadata standard with a semantically enriched instantiation of REMBI (Recommended Metadata for Biological Images). The tabular template provides an easy-to-use practical implementation of REMBI, specifically for High Content Screening (HCS) data. In addition, ISA compliance enables broader integration with other types of experimental data, paving the way for visual omics and multi-Omics integration. We show the utility of MIHCSME for HCS data using multiple examples from the Leiden FAIR Cell Observatory, a Euro-Bioimaging flagship node for high content screening and the pilot node for implementing Findable, Accessible, Interoperable and Reusable (FAIR) bioimaging data throughout the Netherlands Bioimaging network.

Authors 6

1. Rohola Hosseini Aachen Life Science Semantics Leiden Institute of Advanced Computer Science

   Leiden University

   Affiliation as printed

   Life Science Semantics, Leiden Institute of Advanced Computer Science, Leiden, The Netherlands

2. Matthijs Vlasveld Aachen Drug Discovery and Safety Leiden Academic Centre for Drug Research

   Leiden University

   Affiliation as printed

   Drug Discovery and Safety, Cell Observatory, Leiden Academic Centre for Drug Research, Leiden, The Netherlands

3. Joost J. Willemse Aachen Cell Observatory Institute of Biology Leiden

   Leiden University

   Affiliation as printed

   Cell Observatory, Institute of Biology Leiden, Leiden, The Netherlands

4. Bob van de Water Aachen Drug Discovery and Safety Leiden Academic Centre for Drug Research

   Leiden University

   Affiliation as printed

   Drug Discovery and Safety, Cell Observatory, Leiden Academic Centre for Drug Research, Leiden, The Netherlands

5. Sylvia E. Le Dévédec corresponding Aachen Drug Discovery and Safety Leiden Academic Centre for Drug Research

   Leiden University

   Affiliation as printed

   Drug Discovery and Safety, Cell Observatory, Leiden Academic Centre for Drug Research, Leiden, The Netherlands. s.e.ledevedec@lacdr.leidenuniv.nl

   Drug Discovery and Safety, Cell Observatory, Leiden Academic Centre for Drug Research, Leiden, The Netherlands

6. Katherine Wolstencroft corresponding Aachen Life Science Semantics Leiden Institute of Advanced Computer Science

   Leiden University

   Affiliation as printed

   Life Science Semantics, Leiden Institute of Advanced Computer Science, Leiden, The Netherlands. k.j.wolstencroft@liacs.leidenuniv.nl

   Life Science Semantics, Leiden Institute of Advanced Computer Science, Leiden, The Netherlands