Identifying differentially expressed genes (DEGs) is a core task of transcriptome analysis, as DEGs can reveal the molecular mechanisms underlying biological processes. However, interpreting the biological significance of large DEG lists is challenging. Currently, gene ontology, pathway enrichment and protein–protein interaction analysis are common strategies employed by biologists. Additionally, emerging analytical strategies/approaches (such as network module analysis, knowledge graph, drug repurposing, cell marker discovery, trajectory analysis, and cell communication analysis) have been proposed. Despite these advances, comprehensive guidelines for systematically and thoroughly mining the biological information within DEGs remain lacking.

中文翻译：

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从差异表达基因中解锁生物学见解：概念、方法和未来前景


鉴定差异表达基因 （DEG） 是转录组分析的核心任务，因为 DEG 可以揭示生物过程背后的分子机制。然而，解释大型 DEG 列表的生物学意义具有挑战性。目前，基因本体论、通路富集和蛋白质-蛋白质相互作用分析是生物学家采用的常见策略。此外，还提出了新兴的分析策略/方法（如网络模块分析、知识图谱、药物再利用、细胞标志物发现、轨迹分析和细胞通讯分析）。尽管取得了这些进展，但仍然缺乏系统、彻底挖掘 DEG 中生物信息的综合指南。