Chad a Davis (12 results)

Condition: Very Good. Former library copy. Pages intact with possible writing/highlighting. Binding strong with minor wear. Dust jackets/supplements may not be included. Includes library markings. Stock photo provided. Product includes identifying sticker. Better World Books: Buy Books. Do Good.

Taschenbuch. Condition: Neu. Automated protein complex modelling | Computational assembly of macromolecules using heterogeneous structural templates | Chad A. Davis | Taschenbuch | 100 S. | Englisch | 2015 | Südwestdeutscher Verlag für Hochschulschriften | EAN 9783838123769 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.…

Condition: New.

Condition: New.

Condition: New. This is a Brand-new US Edition. This Item may be shipped from US or any other country as we have multiple locations worldwide.

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Gebunden. Condition: New. &Uumlber den AutorProfessor, Division of Athletic Training, School of Applied Health Sciences and Wellness, College of Health Sciences and Professions, Ohio University, Athens, OH.

Condition: New. In English.

Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Protein interaction networks provide an increasingly complex picture of the relationships between macromolecules in the cell. Complementing these interactions with structural data provides critical insights into interaction mechanisms. However, structural information is available only for a tiny fraction of protein interactions and complexes currently known. A method is developed here to predict macromolecular complex structures by systematic combination of pairwise interactions of known structure. An efficient algorithm was designed that exploits heuristics to reduce the large search space. This is complemented with an automated scoring system to filter out the exponentially large number of unrealistic complexes, leaving a ranked set of the most plausible models. On a benchmark set of complexes of known structure, many complexes can be re-created with high accuracy and certain models are much larger and more complete than what is possible with traditional modelling techniques. As the rate of structurally resolved interactions grows, the ability to model larger and more diverse complexes will grow exponentially. 100 pp. Englisch.…

Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Protein interaction networks provide an increasingly complex picture of the relationships between macromolecules in the cell. Complementing these interactions with structural data provides critical insights into interaction mechanisms. However, structural information is available only for a tiny fraction of protein interactions and complexes currently known. A method is developed here to predict macromolecular complex structures by systematic combination of pairwise interactions of known structure. An efficient algorithm was designed that exploits heuristics to reduce the large search space. This is complemented with an automated scoring system to filter out the exponentially large number of unrealistic complexes, leaving a ranked set of the most plausible models. On a benchmark set of complexes of known structure, many complexes can be re-created with high accuracy and certain models are much larger and more complete than what is possible with traditional modelling techniques. As the rate of structurally resolved interactions grows, the ability to model larger and more diverse complexes will grow exponentially.…

Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Davis Chad A.Chad A. Davis, Ph.D., received a B.S.E. in Computer Science and Engineering from Northern Arizona University, an M.Sc. in Bioinformatics from the joint program at the Ludwig-Maximilian University of Munich and the Techn.…

Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Protein interaction networks provide an increasingly complex picture of the relationships between macromolecules in the cell. Complementing these interactions with structural data provides critical insights into interaction mechanisms. However, structural information is available only for a tiny fraction of protein interactions and complexes currently known. A method is developed here to predict macromolecular complex structures by systematic combination of pairwise interactions of known structure. An efficient algorithm was designed that exploits heuristics to reduce the large search space. This is complemented with an automated scoring system to filter out the exponentially large number of unrealistic complexes, leaving a ranked set of the most plausible models. On a benchmark set of complexes of known structure, many complexes can be re-created with high accuracy and certain models are much larger and more complete than what is possible with traditional modelling techniques. As the rate of structurally resolved interactions grows, the ability to model larger and more diverse complexes will grow exponentially.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 100 pp. Englisch.…