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Probing protein folding dynamics using multivariate statistical techniques

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dc.contributor.coauthorPalazoglu, Ahmet
dc.contributor.departmentDepartment of Computer Engineering
dc.contributor.departmentDepartment of Chemical and Biological Engineering
dc.contributor.kuauthorArkun, Yaman
dc.contributor.kuauthorErman, Burak
dc.contributor.kuauthorGürsoy, Attila
dc.contributor.schoolcollegeinstituteCollege of Engineering
dc.date.accessioned2024-11-09T23:02:29Z
dc.date.issued2009
dc.description.abstractThe study of protein folding and its ramifications in biological contexts is at the heart of computational biology. In this paper, we discuss a number of tools in systems engineering that would provide an analysis framework to help explain the observed dynamic behavior of the protein, ultimately making the connection between protein structure and functionality. A case study of villin headpiece folding using principal components analysis as well as clustering demonstrates the potential of these tools in responding to this challenge.
dc.description.indexedbyScopus
dc.description.issuePART 1
dc.description.openaccessYES
dc.description.publisherscopeInternational
dc.description.sponsoredbyTubitakEuN/A
dc.description.volume7
dc.identifier.doi10.3182/20090712-4-tr-2008.00025
dc.identifier.isbn9783-9026-6154-8
dc.identifier.issn1474-6670
dc.identifier.quartileN/A
dc.identifier.scopus2-s2.0-79960940957
dc.identifier.urihttps://doi.org/10.3182/20090712-4-tr-2008.00025
dc.identifier.urihttps://hdl.handle.net/20.500.14288/8295
dc.keywordsClustering
dc.keywordsDynamic simulations
dc.keywordsOptimal folding trajectories
dc.keywordsPrincipal components analysis Chemical analysis
dc.keywordsComputer simulation
dc.keywordsProtein folding
dc.keywordsProteins
dc.keywordsAnalysis frameworks
dc.keywordsClustering
dc.keywordsComputational biology
dc.keywordsDynamic behaviors
dc.keywordsMultivariate statistical techniques
dc.keywordsPrincipal components analysis
dc.keywordsProtein folding dynamics
dc.keywordsProtein structures
dc.keywordsMultivariant analysis
dc.language.isoeng
dc.publisherIFAC
dc.relation.ispartofIFAC Proceedings Volumes (IFAC-PapersOnline)
dc.subjectChemical and biological engineering
dc.titleProbing protein folding dynamics using multivariate statistical techniques
dc.typeConference Proceeding
dspace.entity.typePublication
local.contributor.kuauthorArkun, Yaman
local.contributor.kuauthorGürsoy, Attila
local.contributor.kuauthorErman, Burak
local.publication.orgunit1College of Engineering
local.publication.orgunit2Department of Chemical and Biological Engineering
local.publication.orgunit2Department of Computer Engineering
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relation.isOrgUnitOfPublicationc747a256-6e0c-4969-b1bf-3b9f2f674289
relation.isOrgUnitOfPublication.latestForDiscovery89352e43-bf09-4ef4-82f6-6f9d0174ebae
relation.isParentOrgUnitOfPublication8e756b23-2d4a-4ce8-b1b3-62c794a8c164
relation.isParentOrgUnitOfPublication.latestForDiscovery8e756b23-2d4a-4ce8-b1b3-62c794a8c164

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