PlagueKD: a knowledge graph–based plague knowledge database. (22nd November 2022)

• Record Type: Journal Article
• Authors: Li, Jin; Gao, Jing; Feng, Baiyang; Jing, Yi
• Is Part Of: Database. Volume 2022(2022)
• Publication Date: 2022-11-22
• Subjects: Biology -- Databases -- Periodicals; Bioinformatics -- Periodicals; 570.285
• DOI: 10.1093/database/baac100
• Languages: English
• ISSNs: 1758-0463

Abstract

Abstract: Plague has been confirmed as an extremely horrific international quarantine infectious disease attributed to Yersinia pestis . It has an extraordinarily high lethal rate that poses a serious hazard to human and animal lives. With the deepening of research, there has been a considerable amount of literature related to the plague that has never been systematically integrated. Indeed, it makes researchers time-consuming and laborious when they conduct some investigation. Accordingly, integrating and excavating plague-related knowledge from considerable literature takes on a critical significance. Moreover, a comprehensive plague knowledge base should be urgently built. To solve the above issues, the plague knowledge base is built for the first time. A database is built from the literature mining based on knowledge graph, which is capable of storing, retrieving, managing and accessing data. First, 5388 plague-related abstracts that were obtained automatically from PubMed are integrated, and plague entity dictionary and ontology knowledge base are constructed by using text mining technology. Second, the scattered plague-related knowledge is correlated through knowledge graph technology. A multifactor correlation knowledge graph centered on plague is formed, which contains 9633 nodes of 33 types (e.g. disease, gene, protein, species, symptom, treatment and geographic location), as well as 9466 association relations (e.g. disease–gene, gene–protein and disease–species). The Neo4j graph database is adopted to store and manage the relational data in the form of triple. Lastly, a plague knowledge base is built, which can successfully manage and visualize a large amount of structured plague-related data. This knowledge base almost provides an integrated and comprehensive plague-related knowledge. It should not only help researchers to better understand the complex pathogenesis and potential therapeutic approaches of plague but also take on a key significance to reference for exploring potential action mechanisms of corresponding drug candidates and the development of vaccine in the future. Furthermore, it is of great significance to promote the field of plague research. Researchers are enabled to acquire data more easily for more effective research. Database URL : http://39.104.28.169:18095/