A simple, multivariable and linearly initialized clustering is shown to be able to deal with unsupervised classification of the data originating from pancreatic endocrine tumors (PET). Results are discussed almost only on the data science side, leaving a more biological discussion to future work, even in the quest of possible hidden pathways.

Clustering of pancreatic endocrine tumors via microarray gene expression analysis

2016

Abstract

A simple, multivariable and linearly initialized clustering is shown to be able to deal with unsupervised classification of the data originating from pancreatic endocrine tumors (PET). Results are discussed almost only on the data science side, leaving a more biological discussion to future work, even in the quest of possible hidden pathways.
2016
Istituto di Elettronica e di Ingegneria dell'Informazione e delle Telecomunicazioni - IEIIT
Microarray data - PDDP+K-means clustering - Gene selection - Linear Multivariable Classification
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/302897
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