“食管癌”（EC）是一种高度侵袭性且致命的复杂疾病。它包括两种类型：食管腺癌（EAC）和食管鳞状细胞癌（ESCC），其中巴雷特食管（BE）是唯一已知的癌前病变。最近的研究表明，微小RNA（miRNA）在EC的发生、预后和治疗中发挥着至关重要的作用，并参与多种人类疾病。生物数据库对于癌症研究至关重要，因为它们提供有关基因、蛋白质、途径及其相互作用的信息。这些数据库收集、存储和管理大量分子数据，可用于识别模式、预测结果和生成假设。然而，不存在关于 EC 和 miRNA 关系的综合数据库。为了解决这一差距，我们开发了一个名为“ESOMIR（食管癌中的 miRNA）（https://esomir.dqweilab-sjtu.com）”的动态数据库，其中包括与 EC 相关的目标基因和 miRNA 的信息。该数据库使用分析和预测方法，包括实验认可的 miRNA 信息。 ESOMIR 是一个用户友好的界面，可以通过搜索 miRNA、靶基因、序列、染色体位置和相关信号通路轻松访问 EC 相关数据。搜索模块旨在根据用户的要求向其提供特定的数据访问。此外，该数据库还提供有关网络相互作用、信号传导途径的信息以及与 3' 非翻译区 (3'UTR) 或 5'UTR 和外显子位点相关的染色体区域信息。用户还可以获取具有目标基因的特定 miRNA 的能量水平。每个模块中都包含模糊术语搜索，以提高研究人员的易用性。 ESOMIR 可以成为研究人员和临床医生深入了解 EC 的宝贵工具，包括识别这种侵袭性肿瘤的生物标志物和治疗方法。数据库 URL https://esomir.dqweilab-sjtu.com.© 作者 2023。由牛津大学出版社出版。

'Esophageal cancer' (EC) is a highly aggressive and deadly complex disease. It comprises two types, esophageal adenocarcinoma (EAC) and esophageal squamous cell carcinoma (ESCC), with Barrett's esophagus (BE) being the only known precursor. Recent research has revealed that microRNAs (miRNAs) play a crucial role in the development, prognosis and treatment of EC and are involved in various human diseases. Biological databases have become essential for cancer research as they provide information on genes, proteins, pathways and their interactions. These databases collect, store and manage large amounts of molecular data, which can be used to identify patterns, predict outcomes and generate hypotheses. However, no comprehensive database exists for EC and miRNA relationships. To address this gap, we developed a dynamic database named 'ESOMIR (miRNA in esophageal cancer) (https://esomir.dqweilab-sjtu.com)', which includes information about targeted genes and miRNAs associated with EC. The database uses analysis and prediction methods, including experimentally endorsed miRNA(s) information. ESOMIR is a user-friendly interface that allows easy access to EC-associated data by searching for miRNAs, target genes, sequences, chromosomal positions and associated signaling pathways. The search modules are designed to provide specific data access to users based on their requirements. Additionally, the database provides information about network interactions, signaling pathways and region information of chromosomes associated with the 3'untranslated region (3'UTR) or 5'UTR and exon sites. Users can also access energy levels of specific miRNAs with targeted genes. A fuzzy term search is included in each module to enhance the ease of use for researchers. ESOMIR can be a valuable tool for researchers and clinicians to gain insight into EC, including identifying biomarkers and treatments for this aggressive tumor. Database URL https://esomir.dqweilab-sjtu.com.© The Author(s) 2023. Published by Oxford University Press.