挖掘基因表达数据在肝细胞癌（HCC）中发现新的生物标记和治疗靶点具有重要价值。尽管已经有一些新兴的数据挖掘工具可用于全癌种相关的基因数据分析，但是针对HCC的工具相对较少。此外，专门设计用于HCC的工具存在数据规模较小和功能有限等限制。因此，我们开发了一种新的交互式网络服务器——IHGA，用于在大规模和全面的基础上发现HCC中感兴趣的基因。整合HCC基因分析（IHGA）包含超过100个独立的HCC患者衍生的数据集（共计超过10000个组织样本）和90多个细胞模型。IHGA允许用户基于基因mRNA水平进行一系列大规模和全面的分析和数据可视化，包括表达比较、相关分析、临床特征分析、生存分析、免疫系统相互作用分析和药物敏感性分析。这一方法显著增加了IHGA中的临床数据丰富性。此外，IHGA还整合了基于自然语言模型的人工智能辅助基因筛选。IHGA是免费、用户友好的，能够有效减少数据收集、组织和分析所需的时间。总之，从数据规模、数据多样性和功能性角度来看，IHGA具有竞争力。它有效地减轻了HCC异质性对数据挖掘工作的障碍，并有助于推动HCC分子机制的研究。© 2023作者。

Mining gene expression data is valuable for discovering novel biomarkers and therapeutic targets in hepatocellular carcinoma (HCC). Although emerging data mining tools are available for pan-cancer-related gene data analysis, few tools are dedicated to HCC. Moreover, tools specifically designed for HCC have restrictions such as small data scale and limited functionality. Therefore, we developed IHGA, a new interactive web server for discovering genes of interest in HCC on a large-scale and comprehensive basis. Integrative HCC Gene Analysis (IHGA) contains over 100 independent HCC patient-derived datasets (with over 10,000 tissue samples) and more than 90 cell models. IHGA allows users to conduct a series of large-scale and comprehensive analyses and data visualizations based on gene mRNA levels, including expression comparison, correlation analysis, clinical characteristics analysis, survival analysis, immune system interaction analysis, and drug sensitivity analysis. This method notably enhanced the richness of clinical data in IHGA. Additionally, IHGA integrates artificial intelligence (AI)-assisted gene screening based on natural language models. IHGA is free, user-friendly, and can effectively reduce time spent during data collection, organization, and analysis. In conclusion, IHGA is competitive in terms of data scale, data diversity, and functionality. It effectively alleviates the obstacles caused by HCC heterogeneity to data mining work and helps advance research on the molecular mechanisms of HCC.© 2023 The Authors.