Division of Biology and Biological Engineering 156-29, California Institute of Technology, 1200 E California Blvd, Pasadena, CA 91125, USA.
Database (Oxford). 2021 Mar 31;2021. doi: 10.1093/database/baab015.
Finding relevant information from newly published scientific papers is becoming increasingly difficult due to the pace at which articles are published every year as well as the increasing amount of information per paper. Biocuration and model organism databases provide a map for researchers to navigate through the complex structure of the biomedical literature by distilling knowledge into curated and standardized information. In addition, scientific search engines such as PubMed and text-mining tools such as Textpresso allow researchers to easily search for specific biological aspects from newly published papers, facilitating knowledge transfer. However, digesting the information returned by these systems-often a large number of documents-still requires considerable effort. In this paper, we present Wormicloud, a new tool that summarizes scientific articles in a graphical way through word clouds. This tool is aimed at facilitating the discovery of new experimental results not yet curated by model organism databases and is designed for both researchers and biocurators. Wormicloud is customized for the Caenorhabditis elegans literature and provides several advantages over existing solutions, including being able to perform full-text searches through Textpresso, which provides more accurate results than other existing literature search engines. Wormicloud is integrated through direct links from gene interaction pages in WormBase. Additionally, it allows analysis on the gene sets obtained from literature searches with other WormBase tools such as SimpleMine and Gene Set Enrichment. Database URL: https://wormicloud.textpressolab.com.
从新发表的科学论文中找到相关信息变得越来越困难，这是由于每年发表的文章数量不断增加，以及每篇论文的信息量也在不断增加。生物信息处理和模式生物数据库为研究人员提供了一张地图，通过将知识提炼成经过精心处理和标准化的信息，帮助他们在复杂的生物医学文献结构中进行导航。此外，像 PubMed 这样的科学搜索引擎和像 Textpresso 这样的文本挖掘工具，使研究人员能够轻松地从新发表的论文中搜索特定的生物学方面，促进知识的转移。然而，消化这些系统返回的信息——通常是大量的文档——仍然需要相当大的努力。在本文中，我们介绍了 Wormicloud，这是一种通过词云以图形方式总结科学文章的新工具。该工具旨在帮助发现尚未经过模式生物数据库精心处理的新实验结果，适用于研究人员和生物信息处理人员。Wormicloud 是针对秀丽隐杆线虫文献定制的，与现有的解决方案相比具有几个优势，包括能够通过 Textpresso 进行全文搜索，其提供的结果比其他现有的文献搜索引擎更准确。Wormicloud 通过直接链接从 WormBase 的基因交互页面集成。此外，它还允许使用其他 WormBase 工具（如 SimpleMine 和基因集富集）对从文献搜索中获得的基因集进行分析。数据库网址：https://wormicloud.textpressolab.com。
