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Updated: Jul 31, 2026

JUMPn: A Streamlined Application for Protein Co-Expression Clustering and Network Analysis in Proteomics
Published on: October 19, 2021
Potts ferromagnets on coexpressed gene networks: identifying maximally stable partitions
Himanshu Agrawal1, Eytan Domany
1Department of Physics of Complex Systems, Weizmann Institute of Science, Rehovot 76100, Israel. feagrawa@wicc.weizmann.ac.il
Abstract:
Clustering gene expression data by exploiting phase transitions in granular ferromagnets requires transforming the data to a granular substrate. We present a method using the recently introduced homogeneity order parameter Lambda [H. Agrawal, Phys. Rev. Lett. 89, 268702 (2002)]] for optimizing the parameter controlling the "granularity" and thus the stability of partitions. The model substrates obtained for gene expression data have a highly granular structure. We explore properties of phase transition in high q ferromagnetic Potts models on these substrates and show that the maximum of the width of superparamagnetic domain, corresponding to maximally stable partitions, coincides with the minimum of Lambda.
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