Matthew Hartley

Oct 17, 2024 | embl.org | Matthew Hartley |Christoph Müller |Jan Ellenberg

A closer look at 50 years of imaging developments at EMBL By Matthew Hartley, Christoph Müller, and Jan EllenbergIn the late 1970s, John Kendrew, EMBL’s first Director General, put Swiss biophysicist Jacques Dubochet in charge of the ‘Laboratory for Electron Microscopy Applications’. The aim was to set up methods for carrying out electron microscopy at very, very low temperatures.

Aug 19, 2024 | nature.com | David Horsfall |Daniela Basurto-Lozada |Kenny Roberts |Martin Prete |Peng He |Josh Moore | +5 more

Multimodal tissue atlasing datasets pose two key challenges for online dissemination and equitable access. First, single-cell RNA-sequencing (scRNA-seq) and spatial transcriptomics data objects are often saved in non-unified sequencing and imaging file formats that perform poorly with web technologies. Second, existing software platforms do not readily support simultaneous browsing of multiple integrated data modalities.

Nov 12, 2023 | echo.net.au | Matthew Hartley

So we are going through another ‘housing solution’ meeting are we? Just like the other ones? This will not be resolved, not any more. This will hit a wall and people will be going to jail. The crimes committed and the injustice involved is on a scale such that no solution will present itself. Matthew Hartley, Byron Bay

Sep 14, 2023 | nature.com | Christopher Schmied |Michael Nelson |Sergiy Avilov |Gert-Jan Bakker |Cristina Bertocchi |Johanna Bischof | +39 more

AbstractImages document scientific discoveries and are prevalent in modern biomedical research. Microscopy imaging in particular is currently undergoing rapid technological advancements. However, for scientists wishing to publish obtained images and image-analysis results, there are currently no unified guidelines for best practices. Consequently, microscopy images and image data in publications may be unclear or difficult to interpret.

Jul 11, 2023 | nature.com | Matthew Hartley |Jan Ellenberg

The future of bioimage analysis is increasingly defined by the development and use of tools that rely on deep learning and artificial intelligence (AI). For this trend to continue in a way most useful for stimulating scientific progress, it will require our multidisciplinary community to work together, establish FAIR (findable, accessible, interoperable and reusable) data sharing and deliver usable and reproducible analytical tools.