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Computational Peptidology / edited by Peng Zhou, Jian Huang.

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Holman Biotech Commons QH506 .M45 v.1 (1984)-v.20 (1993),v.22 (1994),v.24 (1994)-v.53 (1996), v.42 (1995) and v.51 (1995) reported missing 3-13-2000 v.55 (1995),v.58 (1996)-v.63 (1997), v.65 (1996)-v.154 (2001), v.156 (2001)-190 (2002), v.192 (2002)-v.407 (2007) v.409 (2007)-v.416 (2008),v.418 (2008)-v.466 v.468-v.490,v.492,v.494,v.496-499 501-506,508,510-512,514,516-517,519-536 538,540-569,571 573-589,591-608,610-615,617,620-627,630-633,636,638,642
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Format:
Book
Contributor:
Zhou, Peng, 1982- editor.
Huang, Jian (Biologist), editor.
SpringerLink (Online service)
Series:
Methods in molecular biology 1064-3745 ; 1268.
Springer Protocols (Springer-12345)
Methods in Molecular Biology, 1064-3745 ; 1268
Language:
English
Subjects (All):
Life sciences.
Proteins.
Bioinformatics.
Computational biology.
Life Sciences.
Protein Science.
Computer Appl. in Life Sciences.
Local Subjects:
Life Sciences.
Protein Science.
Computer Appl. in Life Sciences.
Physical Description:
1 online resource (XI, 338 pages) : 69 illustrations, 43 illustrations in color.
Contained In:
Springer eBooks
Place of Publication:
New York, NY : Springer New York : Imprint: Humana Press, 2015.
System Details:
text file PDF
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.
Contents:
De Novo Peptide Structure Prediction: An Overview
Molecular Modeling of Peptides
Improved Methods for Classification, Prediction, and Design of Antimicrobial Peptides
Building MHC Class II Epitope Predictor Using Machine Learning Approaches
Dynamics (UHBD) Program
Computational Prediction of Short Linear Motifs from Protein Sequences
Peptide Toxicity Prediction
Synthetica Structural Routes For The Rational Conversion of Peptides Into Small Molecules
In Silico Design Of Antimicrobial Peptides
Information-Driven Modelling Of Protein-Peptide Complexes "Information-Driven Peptide Docking"
Computational Approaches To Developing Short Cyclic Peptide Modulators Of Protein-Protein Interactions
A Use of Homology Modeling And Molecular Docking Methods: To Explore Binding Mechanisms of Nonylphenol And Bisphenol a with Antioxidant Enzymes
Computational Peptide Vaccinology
Computational Modeling Of Peptide-Aptamer Binding.
Other Format:
Printed edition:
ISBN:
9781493922857
Access Restriction:
Restricted for use by site license.

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