Coronavirus Disease of 2019 (COVID-19) created dire consequences globally and triggered an enormous scientific effort from different domains. Resulting publications formed a gigantic domain-specific collection of text in which finding studies on a biomolecule of interest is quite challenging for general purpose search engines due to terminology-rich characteristics of the publications. Here, we present Vapur, an online COVID-19 search engine specifically designed for finding related protein-chemical pairs. Vapur is empowered with a biochemically related entities-oriented inverted index in order to group studies relevant to a biomolecule with respect to its related entities. The inverted index of Vapur is automatically created with a BioNLP pipeline and integrated with an online user interface. The online interface is designed for the smooth traversal of the current literature and is publicly available at https://tabilab.cmpe.boun.edu.tr/vapur/ .
翻译:2019年的科罗纳病毒疾病(COVID-19)在全球造成了可怕的后果,并引发了不同领域的大量科学努力,由此的出版物形成了一个庞大的域域特有的文本集,由于这些出版物的术语丰富的特点,对通用搜索引擎来说,查找有关生物分子的研究非常困难,这里我们介绍专门为寻找相关的蛋白-化学配体而设计的在线COVID-19搜索引擎Vapur。Vapur拥有一个以生化相关的实体为导向的反向索引,以便对其相关实体进行与生物分子有关的分组研究。Vapur的倒置索引自动与BioNLP管道创建,并与在线用户界面融合。在线界面是为当前文献的顺利穿透设计,可在https://tbilab.cmpe.boun.edu.tr/vapur/上公开查阅。