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Zibo Chen

@zibochen.bsky.social

135 followers 85 following 11 posts

Assistant professor at Westlake University chenlab.org

Posts Replies Media

Zibo Chen @zibochen.bsky.social · 16/12/2024

Good point on the learning part. Backprop seems difficult to implement using molecules, currently contemplating other means, e.g. the exhaustive search strategy you mentioned, or Hebbian learning

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Zibo Chen @zibochen.bsky.social · 15/12/2024

I am so glad the algorithm has brought me to this gem

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Zibo Chen @zibochen.bsky.social · 15/12/2024

Thank you, Preetham!

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Zibo Chen @zibochen.bsky.social · 13/12/2024

Finally, thanks to Katie Galloway and Christopher Johnstone for this thoughtful perspective. We are indeed excited about the "learning/training" aspect of the Perceptein network! www.science.org/doi/10.1126/...

science.org

Bringing neural networks to life

A synthetic protein-based winner-take-all neural network controls cell fate decisions

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Zibo Chen @zibochen.bsky.social · 13/12/2024

It was tremendous fun brainstorming with @elowitzlab.bsky.social in the early days of this project, and collaborating with all co-authors on this paper. A nice cover art made by the talented Ehmad Chehre:

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Zibo Chen @zibochen.bsky.social · 13/12/2024

3) cleaned up the chemical reaction network diagram (from left to right). Here, each circle is a unique (left) or a group of (right) protein species, and each orange dot represents one (left) or a group of (right) chemical reactions

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Zibo Chen @zibochen.bsky.social · 13/12/2024

2) scaled up the neural network to be 2-input and 3-output, showcasing the scalability of the Perceptein architecture (left, simulation; right, experiments)

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Zibo Chen @zibochen.bsky.social · 13/12/2024

Since our last preprint, we have 1) redirected the classification outcome to cell death, demonstrating the interfacability of protein circuits (thanks to Shiyu Xia)

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Zibo Chen @zibochen.bsky.social · 13/12/2024

As shown in our preprint a while ago, we took a small step further and created a protein circuit, made of de novo designed protein heterodimers and engineered split viral proteases, that carries out weights-tunable winner-take-all neural network computation in mammalian cells.

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Zibo Chen @zibochen.bsky.social · 13/12/2024

This work was inspired by the seminal paper by Cherry and Qian, where they showed one could recognize handwritten digits using DNA molecules in test tubes: www.nature.com/articles/s41...

nature.com

Scaling up molecular pattern recognition with DNA-based winner-take-all neural networks - Nature

DNA-strand-displacement reactions are used to implement a neural network that can distinguish complex and noisy molecular patterns from a set of nine possibilities—an improvement on previous demonstra...

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Zibo Chen @zibochen.bsky.social · 13/12/2024

Excited to finally share Perceptein, a PERCEPtron made of proTEINs: www.science.org/doi/10.1126/...

science.org

A synthetic protein-level neural network in mammalian cells

Artificial neural networks provide a powerful paradigm for nonbiological information processing. To understand whether similar principles could enable computation within living cells, we combined de n...

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