Breathomics is a special branch of metabolomics that quantifies volatile organic compounds (VOCs) from collected exhaled breath samples. Understanding how breath molecules are related to diseases, mechanisms and pathways identified from experimental analytical measurements is challenging due to the lack of an organized resource describing breath molecules, related references and biomedical information embedded in the literature. To provide breath VOCs, related references and biomedical information, we aim to organize a database composed of manually curated information and automatically extracted biomedical information. First, VOCs-related disease information was manually organized from 207 literature linked to 99 VOCs and known Medical Subject Headings (MeSH) terms. Then an automated text mining algorithm was used to extract biomedical information from this literature. In the end, the manually curated information and auto-extracted biomedical information was combined to form a breath molecule database-the Human Breathomics Database (HBDB). We first manually curated and organized disease information including MeSH term from 207 literatures associated with 99 VOCs. Then, an automatic pipeline of text mining approach was used to collect 2766 literatures and extract biomedical information from breath researches. We combined curated information with automatically extracted biomedical information to assemble a breath molecule database, the HBDB. The HBDB is a database that includes references, VOCs and diseases associated with human breathomics. Most of these VOCs were detected in human breath samples or exhaled breath condensate samples. So far, the database contains a total of 913 VOCs in relation to human exhaled breath researches reported in 2766 publications. The HBDB is the most comprehensive HBDB of VOCs in human exhaled breath to date. It is a useful and organized resource for researchers and clinicians to identify and further investigate potential biomarkers from the breath of patients. Database URL: https://hbdb.cmdm.tw.

中文翻译：

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人类呼吸组学数据库。

呼吸组学是代谢组学的一个特殊分支，可对收集的呼出气样本中的挥发性有机化合物（VOC）进行量化。由于缺乏有组织的描述呼吸分子，相关参考文献和文​​献中嵌入的生物医学信息的资源，因此了解呼吸分子与疾病，机制和通过实验分析方法确定的途径之间的关系具有挑战性。为了提供呼吸中的挥发性有机化合物，相关参考资料和生物医学信息，我们旨在组织一个数据库，该数据库由人工策划的信息和自动提取的生物医学信息组成。首先，从207篇文献中手动组织了与VOCs有关的疾病信息，这些文献与99种VOCs和已知的医学主题词（MeSH）术语相关。然后使用自动文本挖掘算法从该文献中提取生物医学信息。最后，将人工策划的信息和自动提取的生物医学信息相结合，形成了一个呼吸分子数据库，即人类呼吸学数据库（HBDB）。我们首先从207篇与99种VOC相关的文献中手动整理和整理了包括MeSH术语在内的疾病信息。然后，使用自动文本挖掘方法管道来收集2766篇文献，并从呼吸研究中提取生物医学信息。我们将精选信息与自动提取的生物医学信息结合起来，建立了呼吸分子数据库HBDB。HBDB是一个数据库，其中包含参考文献，VOC和与人类呼吸动力学相关的疾病。这些VOC中的大多数是在人的呼吸样本或呼出的呼吸冷凝物样本中检测到的。迄今为止，该数据库包含2766篇出版物中报告的与人类呼出气研究相关的913种VOC。HBDB是迄今为止人类呼出气中最全面的VOC HBDB。对于研究人员和临床医生而言，它是有用且有组织的资源，可从患者的呼吸中识别并进一步研究潜在的生物标志物。数据库URL：https：//hbdb.cmdm.tw 对于研究人员和临床医生而言，这是有用且有组织的资源，可从患者的呼吸中识别并进一步研究潜在的生物标志物。数据库URL：https：//hbdb.cmdm.tw 对于研究人员和临床医生而言，它是有用且有组织的资源，可从患者的呼吸中识别并进一步研究潜在的生物标志物。数据库URL：https：//hbdb.cmdm.tw