Studies of cellular dynamic processes have shown that cells undergo state changes during dynamic processes, controlled mainly by the expression of genes within the cell. With the development of high-throughput sequencing technologies, the availability of large amounts of gene expression data enables the acquisition of true gene expression information of cells at the single-cell level. However, most existing research methods require the use of information beyond gene expression, thus introducing additional complexity and uncertainty. In addition, the prevalence of dropout events hampers the study of cellular dynamics. To this end, we propose an approach named gene interaction network entropy (GINE) to quantify the state of cell differentiation as a means of studying cellular dynamics. Specifically, by constructing a cell-specific network based on the association between genes through the stability of the network, and defining the GINE, the unstable gene expression data is converted into a relatively stable GINE. This method has no additional complexity or uncertainty, and at the same time circumvents the effects of dropout events to a certain extent, allowing for a more reliable characterization of biological processes such as cell fate. This method was applied to study two single-cell RNA-seq datasets, head and neck squamous cell carcinoma and chronic myeloid leukaemia. The GINE method not only effectively distinguishes malignant cells from benign cells and differentiates between different periods of differentiation, but also effectively reflects the disease efficacy process, demonstrating the potential of using GINE to study cellular dynamics. The method aims to explore the dynamic information at the level of single cell disorganization and thus to study the dynamics of biological system processes. The results of this study may provide scientific recommendations for research on cell differentiation, tracking cancer development, and the process of disease response to drugs.
Cell Differentiation/genetics* ; Entropy ; Gene Regulatory Networks ; High-Throughput Nucleotide Sequencing ; Single-Cell Analysis/methods*

Objective: To explore and analyze the possible mechanism of liver injury in patients with coronavirus disease 2019 (novel coronavirus pneumonia, NCP). Methods: The correlation between ALT, AST and other liver enzyme changes condition and NCP patients’ disease status reported in the literature was comprehensively analyzed. ACE2 expression in liver tissue for novel coronavirus was analyzed based on single cell sequencing (GSE115469) data. RNA-Seq method was used to analyze Ace2 expression and transcription factors related to its expression in liver tissues at various time-points after hepatectomy in mouse model of acute liver injury with partial hepatectomy. t-test or Spearman rank correlation analysis was used for statistical analysis. Results: ALT and AST were abnormally elevated in some patients with novel coronavirus infection, and the rate and extent of ALT and AST elevation in severe NCP patients were higher than those in non-severe patients. Liver tissue results of single cell sequencing and immunohistochemistry showed that ACE2 was only expressed in bile duct epithelial cells of normal liver tissues, and very low in hepatocytes. In a mouse model of acute liver injury with partial hepatectomy, Ace2 expression was down-regulated on the first day, but it was elevated up to twice of the normal level on the third day, and returned to normal level on seventh day when the liver recovered and hepatocyte proliferation stopped. Whether this phenomenon suggests that the bile duct epithelial cells with positive expression of Ace2 participate in the process of liver regeneration after partial hepatectomy deserves further study. In RNA-Seq data, 77 transcription factors were positively correlated with the expression of ACE2 (r > 0.2, FDR < 0.05), which were mainly enriched in the development, differentiation, morphogenesis and cell proliferation of glandular epithelial cells. Conclusion We assumed that in addition to the over activated inflammatory response in patients with NCP, the up-regulation of ACE2 expression in liver tissue caused by compensatory proliferation of hepatocytes derived from bile duct epithelial cells may also be the possible mechanism of liver tissue injury caused by 2019 novel coronavirus infection.