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231224s2016 xx |||||o 00| ||eng c |
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|a 10.1002/jcc.24474
|2 doi
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|a pubmed24n0882.xml
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|a DE-627
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|c DE-627
|e rakwb
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|a eng
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| 100 |
1 |
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|a Howell, Steven C
|e verfasserin
|4 aut
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| 245 |
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|a Monte Carlo simulation algorithm for B-DNA
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|c 2016
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|a Text
|b txt
|2 rdacontent
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|a ƒaComputermedien
|b c
|2 rdamedia
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|a ƒa Online-Ressource
|b cr
|2 rdacarrier
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| 500 |
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|a Date Completed 30.07.2018
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|a Date Revised 30.07.2018
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|a published: Print
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|a Citation Status MEDLINE
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|a © 2016 Wiley Periodicals, Inc.
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|a Understanding the structure-function relationship of biomolecules containing DNA has motivated experiments aimed at determining molecular structure using methods such as small-angle X-ray and neutron scattering (SAXS and SANS). SAXS and SANS are useful for determining macromolecular shape in solution, a process which benefits by using atomistic models that reproduce the scattering data. The variety of algorithms available for creating and modifying model DNA structures lack the ability to rapidly modify all-atom models to generate structure ensembles. This article describes a Monte Carlo algorithm for simulating DNA, not with the goal of predicting an equilibrium structure, but rather to generate an ensemble of plausible structures which can be filtered using experimental results to identify a sub-ensemble of conformations that reproduce the solution scattering of DNA macromolecules. The algorithm generates an ensemble of atomic structures through an iterative cycle in which B-DNA is represented using a wormlike bead-rod model, new configurations are generated by sampling bend and twist moves, then atomic detail is recovered by back mapping from the final coarse-grained configuration. Using this algorithm on commodity computing hardware, one can rapidly generate an ensemble of atomic level models, each model representing a physically realistic configuration that could be further studied using molecular dynamics. © 2016 Wiley Periodicals, Inc
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|a Journal Article
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| 650 |
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|a Research Support, Non-U.S. Gov't
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| 650 |
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4 |
|a Research Support, U.S. Gov't, Non-P.H.S.
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| 650 |
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4 |
|a Monte Carlo
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| 650 |
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4 |
|a X-ray scattering
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| 650 |
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4 |
|a computer modeling
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| 650 |
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4 |
|a deoxyribonucleic acid
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| 650 |
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4 |
|a molecular mechanics
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| 650 |
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4 |
|a neutron scattering
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| 650 |
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4 |
|a small-angle scattering
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| 650 |
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4 |
|a structural biology
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| 650 |
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7 |
|a DNA, B-Form
|2 NLM
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| 700 |
1 |
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|a Qiu, Xiangyun
|e verfasserin
|4 aut
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| 700 |
1 |
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|a Curtis, Joseph E
|e verfasserin
|4 aut
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| 773 |
0 |
8 |
|i Enthalten in
|t Journal of computational chemistry
|d 1984
|g 37(2016), 29 vom: 05. Nov., Seite 2553-63
|w (DE-627)NLM098138448
|x 1096-987X
|7 nnns
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| 773 |
1 |
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|g volume:37
|g year:2016
|g number:29
|g day:05
|g month:11
|g pages:2553-63
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| 856 |
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|u http://dx.doi.org/10.1002/jcc.24474
|3 Volltext
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