Molecular Subtyping in Human Disease Using the Paraclique Algorithm
Recent discoveries of distinct molecular subtypes have led to remarkable advances in treatment for a variety of diseases. While subtyping via unsupervised clustering has received a great deal of interest, most methods rely on basic statistical or machine learning methods. In this paper we discuss a method based on the paraclique algorithm, and demonstrate its potential effectiveness through testing on four sets of publicly available gene expression microarray data.
KeywordsMolecular subtyping Paraclique Graph algorithms
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