Centre for Genomic & Experimental Medicine
Centre for Genomic & Experimental Medicine

Jason Swedlow (Affiliate)

Tools and capabilities for sharing, accessing and integrating multi-dimensional bioimaging and biomolecular data

Research in a Nutshell

Photo of Professor Jason Swedlow
Professor Swedlow

At the University of Dundee, I lead the Open Microscopy Environment Consortium, an open source specification and software project that builds tools for accessing and sharing complex, heterogenous multi-dimensional datasets.  We use OME’s tools to build and run the Image Data Resource, one of the largest collections of public bioimaging data. My wet lab focuses on mechanism that control chromosome segregation at mitosis.  I also lead the National Phenotypic Screening Centre, which provides advanced, high performance image-based phenotypic screening services to labs and companies across Europe.

In Wellcome Leap’s Tissue Program, we aim to build a “tissue time machine” that predicts how human tissues will change during disease to give researchers, clinicians and patients an accurate prediction of disease progression.

Links

Open Microscopy Environment Consortium (external website)

Wellcome Leap’s Tissue Program (external website)

Contact

jrswedlow@dundee.ac.uk

Collaborations

  • Alvis Brazma, Ugis Sarkans, and Matthew Hartley, EMBL-EBI
  • Angus Lamond and Melpi Platani, Univ Dundee, University of Dundee
  • Jian Ma, Carnegie-Mellon University
  • European Lead Factory—several EU CROs, biotechs and pharma

Publications

Image Data Resource: A Bioimage Data Integration and Publication Platform

June 2017 in Nature Methods

DOI: 10.1038/nmeth.4326

Numerically enhanced adaptive optics-based 3D STED microscopy for deep-tissue super-resolved imaging

December 2019 in ACS Nano

DOI: 10.1021/acsnano.9b05891. PMID: 31841303

A Global View of Standards for Open Image Data Formats and Repositories

May 2021 in Nature Methods 

DOI: 10.1038/s41592-021-01113-7

OME-NGFF: a next-generation file format for expanding bioimaging data strategies

November 2021 in Nature Methods

DOI: 10.1038/s41592-021-01326-w

View all publications on Google Scholar

 

Scientific Themes

Imaging and Image informatics, cell division, public data resources

Technology Expertise

Imaging, open source software development, cell division, high content screening