Candidate Gene Discriminating Gliomas Identification via a Supervised Iteration of Bipartitive k-Means Initialised via Partititve Division According to Principal Components

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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.

WSEAS Transactions on Biology and Biomedicine, ISSN / E-ISSN: 1109-9518 / 2224-2902, Volume 15, 2018, Art. #10

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Rossella Melchiotti, Diego Liberati, "Candidate Gene Discriminating Gliomas Identification via a Supervised Iteration of Bipartitive k-Means Initialised via Partititve Division According to Principal Components," WSEAS Transactions on Biology and Biomedicine, vol. 15, pp. 87-100, 2018, DOI:
Rossella Melchiotti, Diego Liberati. Candidate Gene Discriminating Gliomas Identification via a Supervised Iteration of Bipartitive k-Means Initialised via Partititve Division According to Principal Components. WSEAS Transactions on Biology and Biomedicine. 2018;15:87-100.
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