Dr. Jason Swedlow serves as Chief Executive Officer and President of Glencoe Software, Inc. Dr. Swedlow is co-founder of OME. Dr. Swedlow established his own laboratory at the Wellcome Trust Biocentre, University of Dundee, Scotland as a Principal Investigator and Wellcome Trust Career Development Fellow in 1998. His lab focuses on studies of mitotic and interphase chromosome structure and dynamics. He serves as Co-Director of the Analytical and Quantitative Microscopy Course. Dr. Swedlow was a postdoctoral fellow at UCSF and then Harvard Medical School from 1994 and 1998, supported by a Damon Runyon Walter Winchell Cancer Research Fund Fellowship from 1995 to 1997. He was awarded a Wellcome Trust Senior Fellowship in 2002, and named Professor of Quantitative Cell Biology in 2007. He earned a BA in Chemistry from Brandeis University in 1982. He obtained his PhD in Biophysics in 1994.

OME’s Bio-Formats, OMERO, & IDR: Open Tools for Accessing, Integrating, Mining and Publishing Image Data @ Scale

Mon 17 Sep 2018 3:00pm4:00pm


QBI Large Seminar Room

Despite significant advances in biological imaging and analysis, major informatics challenges remain unsolved: file formats are proprietary, storage and analysis facilities are lacking, as are standards for sharing image data and results. The Open Microscopy Environment (OME) is an open-source software framework developed to address these challenges. OME releases specifications and software for managing image datasets and integrating them with other scientific data. OME’s Bio-Formats and OMERO are used in 1000’s of labs worldwide to enable discovery with imaging.

We have used Bio-Formats and OMERO to build solutions for sharing and publishing imaging data. The Image Data Resource (IDR) includes image data linked to >40 independent studies from genetic, RNAi, chemical, localisation and geographic high content screens, super-resolution microscopy, and digital pathology. Datasets range from several GBs to tens of TBs. Wherever possible, we have integrated image data with all relevant experimental, imaging and analytic metadata. With this metadata integration, we have run queries across studies to identify gene networks that link to cellular phenotypes. We have also built cloud-based analysis tools portals to catalyse the re-use and re-analysis of published imaging data.

With these tools, we aim to build the resources that enable a new kind of bioinformatics that connects molecules and phenotypes across all the scales relevant to biology and medicine.