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The Resource Computational peptidology, edited by Peng Zhou, Jian Huang

Computational peptidology, edited by Peng Zhou, Jian Huang

Label
Computational peptidology
Title
Computational peptidology
Statement of responsibility
edited by Peng Zhou, Jian Huang
Contributor
Editor
Subject
Genre
Language
eng
Summary
In this volume expert researchers detail "in silico" methods widely used to study peptides. These include methods and techniques covering the database, molecular docking, dynamics simulation, data mining, de novo design and structure modeling of peptides and protein fragments. Chapters focus on integration and application of technologies to analyze, model, identify, predict, and design a wide variety of bioactive peptides, peptide analogues and peptide drugs, as well as peptide-based biomaterials. Written in the highly successful "Methods in Molecular Biology" series format, chapters include introductions to their respective topics, lists of the necessary materials and reagents, step-by-step, readily reproducible laboratory protocols, and key tips on troubleshooting and avoiding known pitfalls. Authoritative and practical, "Computational Peptidology" seeks to aid scientists in the further study into this newly rising subfield
Member of
Cataloging source
GW5XE
Illustrations
illustrations
Index
index present
Literary form
non fiction
Nature of contents
  • dictionaries
  • bibliography
Series statement
Methods in Molecular Biology,
Series volume
1268
Computational peptidology, edited by Peng Zhou, Jian Huang
Label
Computational peptidology, edited by Peng Zhou, Jian Huang
Link
http://libproxy.rpi.edu/login?url=http://link.springer.com/10.1007/978-1-4939-2285-7
Publication
Copyright
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Related Location
Related Agents
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Related Subjects
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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
  • Brownian dynamics simulation of peptides with the University of Houston Brownian Dynamics (UHBD) program
  • Tongye Shen and Chung F. Wong
  • Computational prediction of short linear motifs from protein sequences
  • Richard J. Edwards and Nicolas Palopoli
  • Peptide toxicity prediction
  • Sudheer Gupta [and five others]
  • Synthetic and structural routes for the rational conversion of peptides into small molecules
  • Pasqualina Liana Scognamiglio, Giancarlo Morelli, and Daniela Marasco
  • In silico design of antimicrobial peptides
  • Giuseppe Maccari, Mariagrazia Di Luca, and Riccardo Nifosì
  • De novo peptide structure prediction : an overview
  • Information-driven modeling of protein-peptide complexes
  • Mikael Trellet, Adrien S.J. Melquiond, and Alexandre M.J.J. Bonvin
  • Computational approaches to developing short cyclic peptide modulators of protein-protein interactions
  • Fergal J. Duffy, Marc Devocelle, and Denis C. Shields
  • A use of homology modeling and molecular docking methods : to explore binding mechanisms of nonylphenol and bisphenol A with antioxidant enzymes
  • Mannu Jayakanthan [and three others]
  • Computational peptide vaccinology
  • Johannes Söllner
  • Computational modeling of peptide-aptamer binding
  • Kristen L. Rhinehardt, Ram V. Mohan, and Goundla Srinivas
  • Pierre Thévenet [and three others]
  • Molecular modeling of peptides
  • Krzysztof Kuczera
  • Improved methods for classification, prediction, and design of antimicrobial peptides
  • Guangshun Wang
  • Building MHC class II epitope predictor using machine learning approaches
  • Loan Ping Eng, Tin Wee Tan, and Joo Chuan Tong
http://library.link/vocab/cover_art
https://contentcafe2.btol.com/ContentCafe/Jacket.aspx?Return=1&Type=S&Value=9781493922840&userID=ebsco-test&password=ebsco-test
Dimensions
unknown
http://library.link/vocab/discovery_link
{'f': 'http://opac.lib.rpi.edu/record=b3653520'}
Extent
1 online resource (xi, 338 pages)
File format
unknown
Form of item
online
Isbn
9781493922840
Lccn
2014958477
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

    • Folsom LibraryBorrow it
      110 8th St, Troy, NY, 12180, US
      42.729766 -73.682577
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