Discover and read the best of Twitter Threads about #cytoself
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📢 Very excited to see our work #cytoself now published in @naturemethods . #cytoself is a deep learning method for fully self-supervised protein localization profiling and clustering. Led by @liilii_tweet with @kchev @LeonettiManuel at @czbiohub
nature.com/articles/s4159…
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nature.com/articles/s4159…
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Everything started with a conversation with my friend & colleague @LeonettiManuel who worked on building #OpenCellCZB — a map of the human proteome:
opencell.czbiohub.org
We wondered, can we use #DeepLearning to map the landscape of protein sub-cellular localization?
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opencell.czbiohub.org
We wondered, can we use #DeepLearning to map the landscape of protein sub-cellular localization?
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The problem with #images , compared to #sequences, is that it is unclear how to compare them. For example, how to estimate localization similarity from pairs of images of fluorescently labeled cells? With sequences we have algorithms and tools. But for images?
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Endogenous tagging + 3D live-cell imaging + mass-spec interactome = opencell.czbiohub.org, an open-source map of the human proteome. So excited for our first release, wonderful collaboration with @labs_mann @loicaroyer & many other colleagues. @OpenCellCZB
(2/8) We used endogenous #CRISPR tagging with fluorescent probes to map both localization and interactions of proteins in their native cellular context.
(3/8) We built a fully interactive website to share all of our data, including an intuitive 2D/3D viewer for microscopy images: opencell.czbiohub.org
Shout-out to @kchev for web design & engineering
#opendata #opensource
Shout-out to @kchev for web design & engineering
#opendata #opensource
