Thursday, April 18, 2013

Genius at work

Stephen Smale gave a lecture today in the MSU math department, on protein binding and folding. He mainly presented the mathematical aspects and it was a bit like magic. If (as claimed) his methods, which could be described as coming from machine learning, actually give the best results to date on these problems it really is magic.




Title: Mathematics of Protein Folding

Abstract: Learning methods are used to create a geometry on spaces of amino acid sequences. This geometry is used to study immunology, in particular in the peptide binding problem. Then these ideas are used to obtain new results in protein folding.
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5 comments:

  1. Tom9:28 AM

    What's rather surprising is this genius's lackluster undergrad and early graduate performance according to Wikipedia. Not as much of a surprise anymore when one considers the imperfect nature of grades and very likely possibility that Smale probably didn't try hard in math until later in grad school.

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  2. steve hsu9:57 AM

    We actually discussed this earlier in the day. The story is a bit complex. He was a physics major until his senior(?) year, when he switched to math. My impression is that he didn't really apply himself to things he wasn't interested in.

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  3. Jordan Fisher11:20 AM

    My brief excursion into the (applied) math of protein folding suggested to me that the current state of the art is almost fully ad hoc. The "correct" underlying models require so much manipulation, simplification, and judicious use of assumptions in order to arrive at a usable approximation that it's no surprise that, (1), it takes some of the brightest mathematicians/physicists we have to make progress, and, (2), that a computer learning algorithm would probably be needed to sort out all the complexity in a useful way.


    Are there any links available to the talk or related papers?

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