Potts ferromagnets on coexpressed gene networks: Identifying maximally stable partitions
Potts ferromagnets on coexpressed gene networks: Identifying maximally stable partitions
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DOI：
10.1103/physrevlett.90.158102
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发表时间：
2003-04-18
影响因子：
8.6
通讯作者：
Domany, E
中科院分区：
文献类型：
--
作者：
Agrawal, H;Domany, E
通过利用颗粒铁磁体中的相变对基因表达数据进行聚类需要将数据转换为颗粒基质。我们提出了一种使用最近引入的齐次序参量λ [H. Agrawal，Phys. Rev. Lett. 89，268702（2002）]，用于优化控制“粒度”的参数，从而优化分区的稳定性。获得的基因表达数据的模型基板具有高度粒状结构。我们探讨这些基板上的高Q铁磁Potts模型的相变特性，并表明，超顺磁畴的宽度的最大值，对应于最大稳定分区，与最小的Lambda相吻合。
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.