Digging deep into Golgi phenotypic diversity with unsupervised machine learning
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DOI: 10.1091/mbc.e17-06-0379
Abstract: Structural alterations of the Golgi apparatus may lead to phenotypes that human vision cannot easily discriminate. In this work, we present a high-content analysis framework including an unsupervised clustering step to automatically uncover Golgi phenotypic… read more here.
Keywords: digging deep; golgi phenotypic; phenotypic diversity;