Cell type-specific gene expression patterns are represented as memory states of a Hopfield neural network model. It is shown that order parameters of this model can be interpreted as concentrations of master transcription regulators that form concurrent positive feedback loops with a large number of downstream regulated genes. The order parameter free energy then defines an epigenetic landscape in which local minima correspond to stable cell states. The model is applied to gene expression data in the context of hematopoiesis.

中文翻译：

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主调节器作为基因表达状态的顺序参数

细胞类型特异性基因表达模式表示为 Hopfield 神经网络模型的记忆状态。结果表明，该模型的顺序参数可以解释为与大量下游调节基因形成并发正反馈回路的主转录调节因子的浓度。然后，顺序参数自由能定义了一个表观遗传景观，其中局部最小值对应于稳定的细胞状态。该模型应用于造血背景下的基因表达数据。