<efrbr:recordSet xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:efrbr="http://vfrbr.info/efrbr/1.1" xmlns:efrbr-work="http://vfrbr.info/efrbr/1.1/work" xmlns:efrbr-expression="http://vfrbr.info/efrbr/1.1/expression" xmlns:efrbr-manifestation="http://vfrbr.info/efrbr/1.1/manifestation" xmlns:efrbr-person="http://vfrbr.info/efrbr/1.1/person" xmlns:efrbr-corporateBody="http://vfrbr.info/efrbr/1.1/corporateBody" xmlns:efrbr-concept="http://vfrbr.info/efrbr/1.1/concept" xmlns:efrbr-structure="http://vfrbr.info/efrbr/1.1/structure" xmlns:efrbr-responsible="http://vfrbr.info/efrbr/1.1/responsible" xmlns:efrbr-subject="http://vfrbr.info/efrbr/1.1/subject" xmlns:efrbr-other="http://vfrbr.info/efrbr/1.1/other" xsi:schemaLocation="http://vfrbr.info/efrbr/1.1 http://vfrbr.info/schemas/1.1/efrbr.xsd"><efrbr:entities><efrbr-work:work identifier="http://purl.tuc.gr/dl/dias/A98D4390-D293-4671-A62D-2A5BB18BFB18"><efrbr-work:titleOfTheWork>Searching for significant genes in cancer metastasis by tissue comparisons
</efrbr-work:titleOfTheWork></efrbr-work:work><efrbr-expression:expression identifier="http://purl.tuc.gr/dl/dias/A98D4390-D293-4671-A62D-2A5BB18BFB18"><efrbr-expression:titleOfTheExpression>Searching for significant genes in cancer metastasis by tissue comparisons
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            Πλήρης Δημοσίευση σε Συνέδριο
            Conference Full Paper
         </efrbr-expression:formOfExpression><efrbr-expression:dateOfExpression type="issued">2015-10-25</efrbr-expression:dateOfExpression><efrbr-expression:dateOfExpression type="published">2012</efrbr-expression:dateOfExpression><efrbr-expression:languageOfExpression vocabulary="iso639-1">en</efrbr-expression:languageOfExpression><efrbr-expression:summarizationOfContent>DNA Microarrays allow scientists to simultaneously measure the expression levels of thousands of genes. However, an important need arises as to identify those genes closely associated with a particular state of interest, such as cancer, in order to discover useful biological information and efficiently classify new samples. The identification of marker genes is often based on the differential expression of groups of genes and/or their predictive potential manifested in classification experiments. Important aspects that need to be verified on both biological and statistical grounds are the actual problem considered and the algorithmic method selected. In this paper we consider the question of gene differentiation in cancer and how it can be explored through blood sample analysis. We study two algorithmic approaches based on support and relevance vector machines. The results indicate that the latter concept performs better in the specific biological environment, extracting meaningful biological concepts.</efrbr-expression:summarizationOfContent><efrbr-expression:useRestrictionsOnTheExpression type="creative-commons">http://creativecommons.org/licenses/by/4.0/</efrbr-expression:useRestrictionsOnTheExpression><efrbr-expression:note type="page range">594-597</efrbr-expression:note><efrbr-expression:note type="conference name">6th European Conference of the International Federation for Medical and Biological Engineering</efrbr-expression:note></efrbr-expression:expression><efrbr-person:person identifier="http://users.isc.tuc.gr/~mzervakis"><efrbr-person:nameOfPerson vocabulary="TUC:LDAP">
            Zervakis Michalis
            Ζερβακης Μιχαλης
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            Stelios Sfakianakis
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             Dimitris Kafetzopoulos
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            Dimitra Iliopoulou
         </efrbr-person:nameOfPerson></efrbr-person:person><efrbr-person:person identifier="8D50AF23-6520-4537-8AD6-20E7EB73F936"><efrbr-person:nameOfPerson vocabulary="">
            Stelios Sfakianakis
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            Ekaterini S. Bei
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            Springer Verlag
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            Adducts, DNA
            dna adducts
            adducts dna
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            Biomedical scientists
            Health scientists
            medical scientists
            biomedical scientists
            health scientists
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