In this paper, the candidate gene discriminating gliomas identification via a supervised iteration of bipartitive k-mean is presented. Gliomas are supervisedly discriminated by identifying, via iterative bipartitive division according to principal directions initializing k-means, salient genes able to cluster representative patients, thus also giving an insight about degrees of epigenetic similarity among different kinds of gliomas.

Candidate gene discriminating gliomas identification via a supervised iteration of bipartitive k-means initialised via partititve division according to principal components

Diego Liberati
2018

Abstract

In this paper, the candidate gene discriminating gliomas identification via a supervised iteration of bipartitive k-mean is presented. Gliomas are supervisedly discriminated by identifying, via iterative bipartitive division according to principal directions initializing k-means, salient genes able to cluster representative patients, thus also giving an insight about degrees of epigenetic similarity among different kinds of gliomas.
2018
Istituto di Elettronica e di Ingegneria dell'Informazione e delle Telecomunicazioni - IEIIT
K-means
PCA
clustering
salient genes identification
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/361309
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