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dc.contributor.authorAsyali, M.H.
dc.date.accessioned2021-01-25T19:36:52Z
dc.date.available2021-01-25T19:36:52Z
dc.date.issued2007
dc.identifier10.1016/j.compbiomed.2007.04.001
dc.identifier.issn0010-4825
dc.identifier.urihttps://dspace.yasar.edu.tr/xmlui/handle/20.500.12742/8384
dc.description.abstractDue to recent advances in DNA microarray technology, using gene expression profiles, diagnostic category of tissue samples can be predicted with high accuracy. In this study, we discuss shortcomings of some existing gene expression profile classification
dc.language.isoEnglish
dc.publisherPERGAMON-ELSEVIER SCIENCE LTD
dc.titleGene expression profile class prediction using linear Bayesian classifiers
dc.typeArticle
dc.relation.firstpage1690
dc.relation.lastpage1699
dc.relation.volume37
dc.relation.issue12
dc.description.woscategoryBiology; Computer Science, Interdisciplinary Applications; Engineering, Biomedical; Mathematical & Computational Biology
dc.description.wosresearchareaLife Sciences & Biomedicine - Other Topics; Computer Science; Engineering; Mathematical & Computational Biology
dc.identifier.wosidWOS:000251476100002


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