We validated the networks by solving structures for 10 distinct targets (15 maps total). Some directly via segmentation, others by combining the outputs of multiple tools – constraining picks to mitochondria, the nucleus, or the minus end of microtubules, for example.
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Allegretti Lab
This is a two-floor realistic Biological Laboratory building. In this design, I try to tell stories about biologists, introduce biology concepts to general publ…
By making the biological content of cryoET data computationally accessible, easymode helps you screen and explore large datasets and use cellular context to identify particles — enabling flexible approaches to subtomogram averaging.
We're happy to announce our new preprint! 🐸 easymode: general pretrained networks for cellular cryo-ET. Segment ~20 cellular features – ribosomes, microtubules, mitochondria, nuclei & more – with zero model training. 🔗 doi.org/10.64898/202... 🧵👇
