Obiekt

Tytuł: Selecting differentially expressed genes for colon tumor classification

Współtwórca:

Kimmel, Marek - red. ; Lachowicz, Mirosław - red. ; Świerniak, Andrzej - red.

Podtytuł:

Cancer Growth and Progression, Mathematical Problems and Computer Simulations

Tytuł publikacji grupowej:

AMCS, volume 13 (2003)

Abstract:

DNA microarrays provide a new technique of measuring gene expression, which has attracted a lot of research interest in recent years. It was suggested that gene expression data from microarrays (biochips) can be employed in many biomedical areas, e.g., in cancer classification. ; Although several, new and existing, methods of classification were tested, a selection of proper (optimal) set of genes, the expressions of which can serve during classification, is still an open problem. Recently we have proposed a new recursive feature replacement (RFR) algorithm for choosing a suboptimal set of genes. ; The algorithm uses the support vector machines (SVM) technique. In this paper we use the RFR method for finding suboptimal gene subsets for tumor/normal colon tissue classification. The obtained results are compared with the results of applying other methods recently proposed in the literature. ; The comparison shows that the RFR method is able to find the smallest gene subset (only six genes) that gives no misclassifications in leave-one-out cross-validation for a tumor/normal colon data set. In this sense the RFR algorithm outperforms all other investigated methods.

Wydawca:

Zielona Góra: Uniwersytet Zielonogórski

Identyfikator zasobu:

oai:zbc.uz.zgora.pl:59045

Strony:

327-335

Źródło:

AMCS, volume 13, number 3 (2003) ; kliknij tutaj, żeby przejść

Jezyk:

eng

Prawa do dysponowania publikacją:

Biblioteka Uniwersytetu Zielonogórskiego

Obiekty

Podobne

Ta strona wykorzystuje pliki 'cookies'. Więcej informacji