Revision with unchanged content. A powerful new search algorithm, the difference map, has had notable success in many fields that involve finding a characteristic point in a high dimensional search space. The algorithm was first applied to a toy model of proteins in 2004. In that context, the difference map was able to find low energy "folds" better than any contemporary search algorithm. In this work, the same algorithm is applied to a realistic protein model. Though the algorithm finds low energy folds for the protein molecule, the energy function used is found to be inadequate to make the lowest energy state of the protein molecule the native conformation. In this work, the algorithm is described, and some example applications are given. Finally, the complete programming implementation of the algorithm to the problem of protein energy minimization is supplied.

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The author received his B.S. in math and physics from U.C. Davis in 2001, and his PhD in physics from Cornell in 2007. During his studies, he has done experiments on sphere packing in two dimensions, turbulence measurements, computer simulations of superfluid helium vortex's, the subset sum problem, and finally protein structure prediction.

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**Book Description **Book Condition: New. Publisher/Verlag: AV Akademikerverlag | to Protein Structure Prediction | Revision with unchanged content. A powerful new search algorithm, the difference map, has had notable success in many fields that involve finding a characteristic point in a high dimensional search space. The algorithm was first applied to a toy model of proteins in 2004. In that context, the difference map was able to find low energy "folds" better than any contemporary search algorithm. In this work, the same algorithm is applied to a realistic protein model. Though the algorithm finds low energy folds for the protein molecule, the energy function used is found to be inadequate to make the lowest energy state of the protein molecule the native conformation. In this work, the algorithm is described, and some example applications are given. Finally, the complete programming implementation of the algorithm to the problem of protein energy minimization is supplied. | Format: Paperback | Language/Sprache: english | 208 pp. Bookseller Inventory # K9783639440621

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**Book Description **AV Akademikerverlag Jul 2012, 2012. Taschenbuch. Book Condition: Neu. Neuware - Revision with unchanged content. A powerful new search algorithm, the difference map, has had notable success in many fields that involve finding a characteristic point in a high dimensional search space. The algorithm was first applied to a toy model of proteins in 2004. In that context, the difference map was able to find low energy 'folds' better than any contemporary search algorithm. In this work, the same algorithm is applied to a realistic protein model. Though the algorithm finds low energy folds for the protein molecule, the energy function used is found to be inadequate to make the lowest energy state of the protein molecule the native conformation. In this work, the algorithm is described, and some example applications are given. Finally, the complete programming implementation of the algorithm to the problem of protein energy minimization is supplied. 208 pp. Englisch. Bookseller Inventory # 9783639440621

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Published by
AV Akademikerverlag Jul 2012
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ISBN 10: 3639440625
ISBN 13: 9783639440621

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**Book Description **AV Akademikerverlag Jul 2012, 2012. Taschenbuch. Book Condition: Neu. Neuware - Revision with unchanged content. A powerful new search algorithm, the difference map, has had notable success in many fields that involve finding a characteristic point in a high dimensional search space. The algorithm was first applied to a toy model of proteins in 2004. In that context, the difference map was able to find low energy 'folds' better than any contemporary search algorithm. In this work, the same algorithm is applied to a realistic protein model. Though the algorithm finds low energy folds for the protein molecule, the energy function used is found to be inadequate to make the lowest energy state of the protein molecule the native conformation. In this work, the algorithm is described, and some example applications are given. Finally, the complete programming implementation of the algorithm to the problem of protein energy minimization is supplied. 208 pp. Englisch. Bookseller Inventory # 9783639440621

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Published by
AV Akademikerverlag Jul 2012
(2012)

ISBN 10: 3639440625
ISBN 13: 9783639440621

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**Book Description **AV Akademikerverlag Jul 2012, 2012. Taschenbuch. Book Condition: Neu. This item is printed on demand - Print on Demand Neuware - Revision with unchanged content. A powerful new search algorithm, the difference map, has had notable success in many fields that involve finding a characteristic point in a high dimensional search space. The algorithm was first applied to a toy model of proteins in 2004. In that context, the difference map was able to find low energy 'folds' better than any contemporary search algorithm. In this work, the same algorithm is applied to a realistic protein model. Though the algorithm finds low energy folds for the protein molecule, the energy function used is found to be inadequate to make the lowest energy state of the protein molecule the native conformation. In this work, the algorithm is described, and some example applications are given. Finally, the complete programming implementation of the algorithm to the problem of protein energy minimization is supplied. 208 pp. Englisch. Bookseller Inventory # 9783639440621

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Published by
AV Akademikerverlag
(2012)

ISBN 10: 3639440625
ISBN 13: 9783639440621

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**Book Description **AV Akademikerverlag, 2012. Paperback. Book Condition: New. Aufl.. Language: English . Brand New Book. Revision with unchanged content. A powerful new search algorithm, the difference map, has had notable success in many fields that involve finding a characteristic point in a high dimensional search space. The algorithm was first applied to a toy model of proteins in 2004. In that context, the difference map was able to find low energy folds better than any contemporary search algorithm. In this work, the same algorithm is applied to a realistic protein model. Though the algorithm finds low energy folds for the protein molecule, the energy function used is found to be inadequate to make the lowest energy state of the protein molecule the native conformation. In this work, the algorithm is described, and some example applications are given. Finally, the complete programming implementation of the algorithm to the problem of protein energy minimization is supplied. Bookseller Inventory # KNV9783639440621

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