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The Resource Computational protein design, edited by Ilan Samish

Computational protein design, edited by Ilan Samish

Label
Computational protein design
Title
Computational protein design
Statement of responsibility
edited by Ilan Samish
Contributor
Editor
Subject
Language
eng
Summary
The aim this volume is to present the methods, challenges, software, and applications of this widespread and yet still evolving and maturing field. Computational Protein Design, the first book with this title, guides readers through computational protein design approaches, software and tailored solutions to specific case-study targets. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, step-by-step, readily reproducible laboratory protocols, and tips on troubleshooting and avoiding known pitfalls. Authoritative and cutting-edge, Computational Protein Design aims to ensure successful results in the further study of this vital field
Member of
Cataloging source
RML
Illustrations
illustrations
Index
index present
Literary form
non fiction
Nature of contents
  • dictionaries
  • bibliography
Series statement
Methods in molecular biology
Series volume
1529
Computational protein design, edited by Ilan Samish
Label
Computational protein design, edited by Ilan Samish
Link
http://libproxy.rpi.edu/login?url=http://link.springer.com/10.1007/978-1-4939-6637-0
Publication
Copyright
Related Contributor
Related Location
Related Agents
Related Authorities
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Antecedent source
unknown
Bibliography note
Includes bibliographical references and index
Carrier category
online resource
Carrier category code
cr
Carrier MARC source
rdacarrier
Color
multicolored
Content category
text
Content type code
txt
Content type MARC source
rdacontent
Contents
  • Geometric potentials for computational protein sequence design
  • Jie Li and Patrice Koehl
  • Modeling binding affinity of pathological mutations for computational protein design
  • Miguel Romero-Durana, Chiara Pallara, Fabian Glaser, and Juan Fernandez-Recio
  • Multistate computational protein design with backbone ensembles
  • James A. Davey and Roberto A. Chica
  • Integration of molecular dynamics based predictions into the optimization of de novo protein designs : limitations and benefits
  • Henrique F. Carvalho, Armenio J.M. Barbosa, Ana C.A. Roque, Olga Iranzo, and Ricardo J.F. Branco
  • Applications of normal mode analysis methods in computational protein design
  • Vincent Frappier, Matthieu Chartier, and Rafael Najmanovich
  • Framework of computational protein design
  • Computational protein design under a given backbone structure with the ABACUS statistical energy function
  • Peng Xiong, Quan Chen, and Haiyan Liu
  • Computational protein design through grafting and stabilization
  • Cheng Zhu, David D. Mowrey, and Nikolay V. Dokholyan
  • Evolution-based approach to de novo protein design
  • Jeffrey R. Brender, David Shultis, Naureen Aslam Khattak, and Yang Zhang
  • Parallel computational protein design
  • Yichao Zhou, Bruce R. Donald, and Jianyang Zeng
  • BindML/BindML+ : detecting protein-protein interaction interface propensity from amino acid substitution patterns
  • Qing Wei, David La, and Daisuke Kihara
  • Ilan Samish
  • OSPREY predicts resistance mutations using positive and negative computational protein design
  • Adegoke Ojewole, Anna Lowegard, Pablo Gainza, Stephanie M. Reeve, Ivelin Georgiev, Amy C. Anderson, and Bruce R. Donald
  • Evolution-inspired computational design of symmetric proteins
  • Arnout R.D. Voet, David Simoncini, Jeremy R.H. Tame, and Kam Y.J. Zhang
  • Protocol for the design of protein and peptide nanostructure self-assemblies exploiting synthetic amino acids
  • Nurit Haspel, Jie Zheng, Carlos Aleman, David Zanuy, and Ruth Nussinov
  • Probing oligomerized conformations of defensin in the membrane
  • Wenxun Gan, Dina Schneidman, Ning Zhang, Buyong Ma, and Ruth Nussinov
  • Computational design of ligand binding proteins
  • Christine E. Tinberg and Sagar D. Khare
  • Achievements and challenges in computational protein design
  • EpiSweep : computationally driven reengineering of therapeutic proteins to reduce immunogenicity while maintaining function
  • Yoonjoo Choi, Deeptak Verma, Karl E. Griswold, and Chris Bailey-Kellogg
  • Computational tools for aiding rational antibody design
  • Konrad Krawczyk, James Dunbar, and Charlotte M. Deane
  • Computational design of membrane curvature-sensing peptides
  • Armando Jerome de Jesus and Hang Yin
  • Computational tools for allosteric drug discovery : site identification and focus library design
  • Wenkang Huang, Ruth Nussinov, and Jian Zhang
  • Ilan Samish
  • Production of computationally designed small soluble- and membrane-proteins : cloning, expression, and purification
  • Barsa Tripathy and Rudresh Acharya
  • Deterministic search methods for computational protein design
  • Seydou Traore, David Allouche, Isabelle Andre, Thomas Schiex, and Sophie Barbe
http://library.link/vocab/cover_art
https://contentcafe2.btol.com/ContentCafe/Jacket.aspx?Return=1&Type=S&Value=9781493966356&userID=ebsco-test&password=ebsco-test
Dimensions
unknown
http://library.link/vocab/discovery_link
{'f': 'http://opac.lib.rpi.edu/record=b4160374'}
Extent
1 online resource (xii, 450 pages)
File format
unknown
Form of item
online
Isbn
9781493966356
Lccn
2016959982
Level of compression
unknown
Media category
computer
Media MARC source
rdamedia
Media type code
c
Other physical details
illustrations (some color).
Quality assurance targets
not applicable
Reformatting quality
unknown
Sound
unknown sound
Specific material designation
remote

Library Locations

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