>Denny Chen Dai, SFU – An Incremental Redundancy Estimation for the Sequence Neighbourhood Boundary

>Background: RNA primary and secondary structure. Working on the RNA design problem (Inverse RNA folding.) [Ah, the memories…]

Divide into sequence space and structure space. Structure space is smaller than sequence space. (Many to one relationship.)

Biology application: how does sequence mutation change the structure space?

Neighbourhood Ball : Sequences that are closely related, but fold differently. As you get closer to the edge of the ball, you find… [something?]

Method:

  • Sample n sequences with unique mapping strucure
  • for each sample: search neutral sequence within inner layers, redundancy hit?
  • Compute redundancy rate p.
  • Redundancy rate distribution over Hamming layers. P will approach 1. (all structure are redundant.)

The question is at what point do you saturate? Where do you find this boundary? Somewhere around 50% of sequence space. [I think??]

Summary:

  • An efficient estimation boundary – confirmed the existence of the neigborhood ball
  • ball radius is much smaller than the seqeunce length.

Where is this useful?

  • Reduce computational effort for RNA design
  • naturally occurring RNA molecules, faster reduncdancy growth rate suggests mutational robustness.
[My Comment: I really don’t see where this is coming from.  Seems to be kind of silly, doesn’t reference any of the other work in the field that I’m aware of.  (Some of the audience questions seem to agree.)  Overall, I just don’t see what he’s trying to do – I’m not even sure I agree with his results.  I’ll have to check out his poster later to see if I can make sense of it.  Sorry for the poor notes.  ]

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