Publication:
Prediction of folding type of proteins using mixed-integer linear programming

dc.contributor.departmentDepartment of Industrial Engineering
dc.contributor.departmentGraduate School of Sciences and Engineering
dc.contributor.kuauthorTürkay, Metin
dc.contributor.kuauthorYılmaz, Özlem
dc.contributor.kuauthorYüksektepe, Fadime Üney
dc.contributor.schoolcollegeinstituteCollege of Engineering
dc.contributor.schoolcollegeinstituteGRADUATE SCHOOL OF SCIENCES AND ENGINEERING
dc.date.accessioned2024-11-10T00:05:44Z
dc.date.issued2005
dc.description.abstractProteins are classified into four main structural classes by considering their amino acid compositions. Traditional approaches that use hyperplanes to partition data sets into two groups perform poorly due to the existence of four classes. Therefore, a novel method that uses mixed-integer programming is developed to overcome difficulties and inconsistencies of these traditional approaches. Mixed-integer programming (MIP) allows the use of hyper-boxes in order to define the boundaries of the sets that include all or some of the points in that class. For this reason, the efficiency and accuracy of data classification with MIP approach can be improved dramatically compared to the traditional methods. The efficiency of the proposed approach is illustrated on a training set of 120 proteins (30 from each type). The prediction results and their validation are also examined.
dc.description.indexedbyWOS
dc.description.indexedbyScopus
dc.description.openaccessNO
dc.description.sponsoredbyTubitakEuN/A
dc.description.volume20a-20b
dc.identifier.isbn0-444-51987-4
dc.identifier.issn1570-7946
dc.identifier.scopus2-s2.0-35648938963
dc.identifier.urihttps://hdl.handle.net/20.500.14288/16481
dc.identifier.wos233423000086
dc.keywordsData classification
dc.keywordsProtein structure
dc.keywordsMixed-integer linear programming
dc.keywordsAmino-acid-composition
dc.keywordsRecognition
dc.language.isoeng
dc.publisherElsevier Science Bv
dc.relation.ispartofEuropean Symposium on Computer-Aided Process Engineering-15, 20a and 20b
dc.subjectComputer Science
dc.subjectArtificial intelligence
dc.subjectChemical engineering
dc.subjectChemical engineering
dc.subjectOperations research
dc.subjectManagement science
dc.subjectMathematics
dc.titlePrediction of folding type of proteins using mixed-integer linear programming
dc.typeConference Proceeding
dspace.entity.typePublication
local.contributor.kuauthorTürkay, Metin
local.contributor.kuauthorYüksektepe, Fadime Üney
local.contributor.kuauthorYılmaz, Özlem
local.publication.orgunit1College of Engineering
local.publication.orgunit1GRADUATE SCHOOL OF SCIENCES AND ENGINEERING
local.publication.orgunit2Department of Industrial Engineering
local.publication.orgunit2Graduate School of Sciences and Engineering
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