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dc.contributor.authorÖzarar, M.en_US
dc.contributor.authorAtalay, V.en_US
dc.contributor.authorÇetin-Atalay, Rengülen_US
dc.coverage.spatialKuşadası, Turkeyen_US
dc.date.accessioned2016-02-08T11:53:12Z
dc.date.available2016-02-08T11:53:12Z
dc.date.issued2004en_US
dc.identifier.urihttp://hdl.handle.net/11693/27431
dc.descriptionDate of Conference: 28-30 April 2004en_US
dc.descriptionConference Name: IEEE 12th Signal Processing and Communications Applications Conference, SIU 2004en_US
dc.description.abstractSubcellular localization is crucial for determining the functions of proteins. A system called prediction of protein subcellular localization (P2SL) that predicts the subcellular localization of proteins in eukaryotic organisms based on the amino acid content of primary sequences using amino acid order is designed. The approach for prediction is to find the most frequent motifs for each protein in a given class based on clustering via self organizing maps and then to use these most frequent motifs as features for classification by the help of multi layer perceptrons. This approach allows a classification independent of the length of the sequence. In addition to these, the use of a new encoding scheme is described for the amino acids that conserves biological function based on point of accepted mutations (PAM) substitution matrix. The statistical test results of the system is presented on a four class problem. P2SL achieves slightly higher prediction accuracy than the similar studies.en_US
dc.language.isoTurkishen_US
dc.source.titleProceedings of the IEEE 12th Signal Processing and Communications Applications Conference, SIU 2004en_US
dc.relation.isversionofhttps://doi.org/10.1109/SIU.2004.1338272en_US
dc.subjectEncoding schemeen_US
dc.subjectFour class problemen_US
dc.subjectProtein subcellular localization (P2SL)en_US
dc.subjectSubstitution matrixen_US
dc.subjectAmino acidsen_US
dc.subjectCellsen_US
dc.subjectData reductionen_US
dc.subjectMatrix algebraen_US
dc.subjectProblem solvingen_US
dc.subjectSelf organizing mapsen_US
dc.subjectSignal encodingen_US
dc.subjectStatistical methodsen_US
dc.subjectProteinsen_US
dc.titlePrediction of protein subcellular localization based on primary sequence dataen_US
dc.title.alternativeBirincil dizi veri temelli protein hücre içi yer belirleme tahminien_US
dc.typeConference Paperen_US
dc.departmentDepartment of Molecular Biology and Geneticsen_US
dc.citation.spage118en_US
dc.citation.epage120en_US
dc.identifier.doi10.1109/SIU.2004.1338272en_US
dc.publisherIEEEen_US


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