Vapur: A Search Engine to Find Related Protein-Compound Pairs in COVID-19 Literature
September 05, 2020 Β· Declared Dead Β· π bioRxiv
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Authors
Abdullatif KΓΆksal, Hilal DΓΆnmez, RΔ±za ΓzΓ§elik, Elif Ozkirimli, Arzucan ΓzgΓΌr
arXiv ID
2009.02526
Category
cs.IR: Information Retrieval
Cross-listed
cs.LG,
q-bio.MN
Citations
13
Venue
bioRxiv
Last Checked
4 months ago
Abstract
Coronavirus Disease of 2019 (COVID-19) created dire consequences globally and triggered an intense scientific effort from different domains. The resulting publications created a huge text collection in which finding the studies related to a biomolecule of interest is challenging for general purpose search engines because the publications are rich in domain specific terminology. Here, we present Vapur: an online COVID-19 search engine specifically designed to find related protein - chemical pairs. Vapur is empowered with a relation-oriented inverted index that is able to retrieve and group studies for a query 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 by domain researchers and is publicly available at https://tabilab.cmpe.boun.edu.tr/vapur/ .
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