Abstract There is an ongoing need for scalable tools to aid researchers in both retrospective and prospective standardization of discrete entity types—such as disease names, cell types, or chemicals—that are used in metadata associated with biomedical data. When metadata are not well-structured or precise, the associated data are harder to find and are often burdensome to reuse, analyze, or integrate with other datasets due to the upfront curation effort required to make the data usable—typically through retrospective standardization and cleaning of the (meta)data. With the goal of facilitating the task of standardizing metadata—either in bulk or in a one-by-one fashion, e.g. to support autocompletion of biomedical entities in forms—we have developed an open-source tool called text2term that maps free-text descriptions of biomedical entities to controlled terms in ontologies. The tool is highly configurable and can be used in multiple ways that cater to different users and expertise levels—it is available on Python Package Index and can be used programmatically as any Python package; it can also be used via a command-line interface or via our hosted, graphical user interface–based web application or by deploying a local instance of our interactive application using Docker. Database URL: https://pypi.org/project/text2term

Rafael S Gonçalves

Jason Payne

Amelia Tan

Carmen Benitez

Jamie Haddock

Robert Gentleman

Database

大量原始数据存档在众多开放存取数据库中，随着新一代技术在实验室中变得越来越普遍，大型数据集将变得更加普遍。所有这些数据的归档、管理、分析和解释都是一项挑战。数据库开发和生物管理处于努力理解这种不断增加的数据洪流的最前沿。数据库：生物数据库和管理杂志提供了一个开放访问平台，用于展示数据库研究和生物管理中的新思想，旨在帮助加强数据库开发人员、管理者和用户之间的桥梁。

As next-generation technologies become increasingly common in laboratories, a vast amount of raw data is being archived in numerous open-access databases, leading to the prevalence of large datasets. Effectively archiving, managing, analyzing, and interpreting this data presents a significant challenge. Database development and biological management are at the forefront of understanding this growing data deluge. "Database: The Journal of Biological Databases and Curation" offers an open-access platform to showcase new ideas in database research and biological management, aiming to strengthen the connections between database developers, managers, and users.

随着新一代技术在实验室中的普及，越来越多的原始数据被存档在众多开放存取数据库中，导致大型数据集的出现变得愈加普遍。如何有效地归档、管理、分析和解释这些数据，成为了一项巨大的挑战。数据库开发和生物管理正处于理解这一不断增加的数据洪流的前沿。"Database: The Journal of Biological Databases and Curation" 提供了一个开放获取的平台，旨在展示数据库研究和生物管理中的新思想，帮助加强数据库开发者、管理者与用户之间的联系。

Category	Quartile
生物学	4
生物学, 数学与计算生物学	4

The text2term tool to map free-text descriptions of biomedical terms to ontologies

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Journal Info

Category	Quartile
MATHEMATICAL & COMPUTATIONAL BIOLOGY	1