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Matthew Aquilina

@mattaq.bsky.social
115 followers 84 following 7 posts

Postdoctoral Research Fellow @ Wyss Institute/Dana-Farber Cancer Institute/Harvard University in the William Shih Lab Currently doing DNA nanotech research with a sprinkling of AI and software dev!

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Matthew Aquilina @mattaq.bsky.social · 05/05/2025
If you have any feedback on GelGenie or any requests/ideas for new features please let us know - we’re excited to see how GelGenie will fit into your workflow! We’re really grateful for all those who’ve already provided feedback or supported the project throughout the early stages!
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Matthew Aquilina @mattaq.bsky.social · 05/05/2025
GelGenie has already been downloaded 100+ times since the preprint was released and we’ve seen lots of enthusiasm from researchers at our institutions (including winning the ‘Most Innovative Project’ prize at DFCI’s annual Cancer Biology retreat!) and at #FNANO 2025.
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Matthew Aquilina @mattaq.bsky.social · 05/05/2025
- Export directly to csv or to an auto-generated bar graph - Use scripting to analyse multiple images in one go - Make freeform manual edits if necessary - and much more!
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Matthew Aquilina @mattaq.bsky.social · 05/05/2025
Just as a reminder, with GelGenie you can: - One-click extract bands (even wacky ones!) from gels in various imaging conditions, resolutions, contrasts, etc. - Collate your data, apply background correction and normalize the results automatically
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Matthew Aquilina @mattaq.bsky.social · 05/05/2025
Download it now (available for Mac, Windows or Linux) from here: github.com/mattaq31/Gel... A model usable within ImageJ is now also available on BioImage.IO (docs here: github.com/mattaq31/Gel...) #machinelearning #AI #segmentation #imageanalysis #gelelectrophoresis #gelquantification #qupath
github.com
GitHub - mattaq31/GelGenie: Open-Source package for segmentation and analysis of gel electrophoresis images using machine learning. Both a python framework for training/running models and a QuPath GU...
Open-Source package for segmentation and analysis of gel electrophoresis images using machine learning. Both a python framework for training/running models and a QuPath GUI extension are available...
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Matthew Aquilina @mattaq.bsky.social · 05/05/2025
GelGenie has finally been published in Nature Communications (DOI: doi.org/10.1038/s414...)! GelGenie is a free, open-source app for the one-click extraction of band data from gel images using AI, all bundled within a cross-platform GUI that can be integrated in your workflow immediately. 🧬
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Matthew Aquilina @mattaq.bsky.social · 22/11/2024
Would love to be added too, thanks!
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