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SUMMARY:The Sequence-Dependent Statistical Mechanics and Persistence Lengt
 hs of DNA
DTSTART:20160414T163000
DTEND:20160414T173000
DTSTAMP:20260508T174206Z
UID:3cc62d659b77a9034a6f5e7aa5958d7babe54cc7fd43427f0cbabc6d
CATEGORIES:Conferences - Seminars
DESCRIPTION:Prof. John H. Maddocks\nEPFL SB MATHGEOM LCVMM\nMA C1 582 (Bâ
 timent MA)\nStation 8\nCH-1015 Lausanne\nThe recently developed cgDNA sequ
 ence-dependent rigid-base coarse grain model of DNA is parameterised from 
 Molecular Dynamics simulations at the scale of 20bp and less. The sequence
 -dependent ground states predicted by the cgDNA model compare reasonably w
 ell with both NMR and X-ray crystal experimental data. The cgDNA free ener
 gy also allows numerically efficient simulations at much longer length (an
 d time) scales\, for example computation of looping and cyclisation J-fact
 ors. The cgDNA model also allows efficient Monte Carlo sampling of the con
 figuration space equilibrium ensemble for DNA fragments with arbitrarily p
 rescribed sequence at length scales of a few hundred to a few thousand bp 
 and more. These Monte Carlo simulations reveal strong sequence dependence 
 of the classic correlation functions of polymer physics through the effect
  of both intrinsic shape and differing stiffnesses\, and moreover that the
 se two effects can be factored in a simple way. On the other hand when the
  ensem\nble includes averaging over sequence\, the cgDNA Monte Carlo simul
 ations predict the single effective persistence length of 163 bp\, which i
 s in remarkably good agreement with the consensus experimental value of 15
 0 bp or so.\nJoint work with A. Grandchamp\, J. Glowacki\, R. Manning\, an
 d J. Mitchell
LOCATION:CH G1 495 https://plan.epfl.ch/?room==CH%20G1%20495
STATUS:CONFIRMED
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