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Molecular Subtyping in Human Disease Using the Paraclique Algorithm

  • Ronald D. HaganEmail author
  • Michael A. Langston
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 1062)

Abstract

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.

Keywords

Molecular subtyping Paraclique Graph algorithms 

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.BAE SystemsBurlingtonUSA
  2. 2.Department of Electrical Engineering and Computer ScienceUniversity of TennesseeKnoxvilleUSA

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