Cell Learning Theory

• Co-organisers: Michael Chappuis and Dan Murfet.
• Venue: the Research Agora.

Schedule

• 24-2-22 (Dan Murfet): Invitation to natural programs (notes, video).
• 3-3-22 (David Li): Understanding AlphaFold (notes, video).
• 31-3-22 Journal club discussion of “Symmetry and simplicity spontaneously emerge from the algorithmic nature of evolution”.
• 7-4-22 (Hessam Akhlaghpour): “An RNA-Based Theory of Natural Universal Computation”.

Background

• Background on molecular biology from the Stanford Encyclopedia of Philosophy.
• A primer on transcription and mRNA, translation from mRNA to protein and transcriptional regulation.

Here are some other notes:

• Cell Learning Theory 1
• Cell Learning Theory 2

References

• H. Akhlaghpour, “An RNA-Based Theory of Natural Universal Computation”.
• J. Jumper et al “Highly accurate protein structure prediction with AlphaFold” Nature 2021.
• S. Gershman, P. Balbi, C. Gallistel, J. Gunawardena, “Reconsidering the evidence for learning in single cells” Elife 2021.