Difference between revisions of "Lecture 11"
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+ | '''Update Warning!''' | ||
+ | This page has not been revised yet for the 2007 Fall term. Some of the slides may be reused, but please consider the page as a whole out of date as long as this warning appears here. | ||
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__NOTOC__ | __NOTOC__ | ||
<small>[[Lecture_10|(Previous lecture)]] ... [[Lecture_12|(Next lecture)]]</small> | <small>[[Lecture_10|(Previous lecture)]] ... [[Lecture_12|(Next lecture)]]</small> | ||
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======Slide 004====== | ======Slide 004====== | ||
[[Image:L11_s004.jpg|frame|none|Lecture 11, Slide 004<br> | [[Image:L11_s004.jpg|frame|none|Lecture 11, Slide 004<br> | ||
+ | A toy observation on an optimization problem of similar magnitude as the random folding of a protein... | ||
+ | ]] | ||
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======Slide 005====== | ======Slide 005====== | ||
[[Image:L11_s005.jpg|frame|none|Lecture 11, Slide 005<br> | [[Image:L11_s005.jpg|frame|none|Lecture 11, Slide 005<br> | ||
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======Slide 018====== | ======Slide 018====== | ||
[[Image:L11_s018.jpg|frame|none|Lecture 11, Slide 018<br> | [[Image:L11_s018.jpg|frame|none|Lecture 11, Slide 018<br> | ||
+ | Non-polynomial time-complexity problems are considered intractable, since even as the problem size ''''n'''' grows only modestly, the time requirements grow beyond all bounds and reasonable resources. A 1,000 element problem of ''O''(2<sup>''n''</sup>) complexity takes the age of the universe to compute. | ||
+ | ]] | ||
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======Slide 019====== | ======Slide 019====== | ||
[[Image:L11_s019.jpg|frame|none|Lecture 11, Slide 019<br> | [[Image:L11_s019.jpg|frame|none|Lecture 11, Slide 019<br> | ||
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[[Image:L11_s024.jpg|frame|none|Lecture 11, Slide 024<br> | [[Image:L11_s024.jpg|frame|none|Lecture 11, Slide 024<br> | ||
+ | Simulated annealing allows a system to be computationally moved out of situations where it is trapped in local minima, and to proceed towards a global minimum on a rough search landscape. | ||
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======Slide 025====== | ======Slide 025====== | ||
[[Image:L11_s025.jpg|frame|none|Lecture 11, Slide 025<br> | [[Image:L11_s025.jpg|frame|none|Lecture 11, Slide 025<br> | ||
+ | A simulated annealing strategy (in pseudocode). | ||
+ | ]] | ||
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======Slide 026====== | ======Slide 026====== | ||
[[Image:L11_s026.jpg|frame|none|Lecture 11, Slide 026<br> | [[Image:L11_s026.jpg|frame|none|Lecture 11, Slide 026<br> | ||
+ | Many believe that genetic algorithms - albeit interesting - rarely outperform simulated annealing. | ||
+ | ]] | ||
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======Slide 027====== | ======Slide 027====== | ||
[[Image:L11_s027.jpg|frame|none|Lecture 11, Slide 027<br> | [[Image:L11_s027.jpg|frame|none|Lecture 11, Slide 027<br> | ||
+ | Natural proteins of course have evolved under the constraint of foldability. They may have avoided mutations that would expose them to the requirements of full, combinatorial optimization of their 3-D structure. | ||
+ | ]] | ||
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======Slide 028====== | ======Slide 028====== | ||
[[Image:L11_s028.jpg|frame|none|Lecture 11, Slide 028<br> | [[Image:L11_s028.jpg|frame|none|Lecture 11, Slide 028<br> |
Latest revision as of 15:27, 1 September 2007
Update Warning! This page has not been revised yet for the 2007 Fall term. Some of the slides may be reused, but please consider the page as a whole out of date as long as this warning appears here.
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Protein Structure Prediction
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Lecture 11, Slide 018
Non-polynomial time-complexity problems are considered intractable, since even as the problem size 'n' grows only modestly, the time requirements grow beyond all bounds and reasonable resources. A 1,000 element problem of O(2n) complexity takes the age of the universe to compute.
Non-polynomial time-complexity problems are considered intractable, since even as the problem size 'n' grows only modestly, the time requirements grow beyond all bounds and reasonable resources. A 1,000 element problem of O(2n) complexity takes the age of the universe to compute.