In Silico Protein Motif Discovery and Structural Analysis

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Title: In Silico Protein Motif Discovery and Structural Analysis
Authors: Mooney, CatherineDavey, Norman E.Martin, Alberto J. M.Walsh, IanShields, Denis C.Pollastri, Gianluca
Permanent link: http://hdl.handle.net/10197/13126
Date: 30-Jun-2011
Online since: 2022-09-20T15:54:49Z
Abstract: A wealth of in silico tools is available for protein motif discovery and structural analysis. The aim of this chapter is to collect some of the most common and useful tools and to guide the biologist in their use. A detailed explanation is provided for the use of Distill, a suite of web servers for the prediction of protein structural features and the prediction of full-atom 3D models from a protein sequence. Besides this, we also provide pointers to many other tools available for motif discovery and secondary and tertiary structure prediction from a primary amino acid sequence. The prediction of protein intrinsic disorder and the prediction of functional sites and SLiMs are also briefly discussed. Given that user queries vary greatly in size, scope and character, the trade-offs in speed, accuracy and scale need to be considered when choosing which methods to adopt.
Funding Details: Health Research Board
Science Foundation Ireland
Funding Details: EMBL Interdisciplinary Postdoc (EIPOD) fellowship
UCD President's Award
Type of material: Book Chapter
Publisher: Springer
Series/Report no.: Methods in Molecular Biology; 760
Keywords: Protein structure predictionSecondary structureDisorderFunctional sitesSLiMsShort linear motifsStructure predictionSecondary structureSolvent accessibilityFunctional sitesMinimotif minerAb-initioServerWebSequence
DOI: 10.1007/978-1-61779-176-5_21
Language: en
Status of Item: Peer reviewed
Is part of: Yu, B. and Hinchcliffe, M. (eds.). In Silico Tools for Gene Discovery
ISBN: 978-1-61779-175-8
This item is made available under a Creative Commons License: https://creativecommons.org/licenses/by-nc-nd/3.0/ie/
Appears in Collections:Conway Institute Research Collection
Computer Science Research Collection
CASL Research Collection
Medicine Research Collection

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