Journal article
Examining drug and side effect relation using author–entity pair bipartite networks
Journal of informetrics, v 14(1), 100999
Feb 2020
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
•The paper explores the characteristics of biological entities, such as drugs, and their side effects using an author–entity pair bipartite network.•We propose a new ranking algorithm that takes into consideration the characteristics of bipartite networks to identify top-ranked entity pairs.•We compared the drug and side effect pairs obtained from the network containing both drug and side effect with those observed in SIDER.•Our approach was able to identify a wide range of patterns of drug–side effect relations from the perspective of authors’ research interests.
The current study has two objectives. First, we explore the characteristics of biological entities, such as drugs, and their side effects using an author–entity pair bipartite network. Second, we use the constructed network to examine whether there are outstanding features of relations between drugs and side effects. We extracted drug and side effect names from 169,766 PubMed abstracts published between 2010 to 2014 and constructed author–entity pair bipartite networks after ambiguous author names were processed. We propose a new ranking algorithm that takes into consideration the characteristics of bipartite networks to identify top-ranked biological drug and side effect pairs. To investigate the relationship between a particular drug and a side effect, we compared the drug and side effect pairs obtained from the network containing both drug and side effect with those observed in SIDER, a human expert-curated database. The results of this study indicate that our approach was able to identify a wide range of patterns of drug–side effect relations from the perspective of authors’ research interests. Further, our approach also identified the unique characteristics of the relation of biomedical entities obtained using an author–entity pair bipartite network.
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Details
- Title
- Examining drug and side effect relation using author–entity pair bipartite networks
- Creators
- Yoo Kyung Jeong - Center for Modern Korean Studies, Yonsei University, Wonju, Republic of KoreaQing Xie - Department of Library and Information Science, Yonsei University, Seoul, Republic of KoreaErjia Yan - College of Computing and Informatics, Drexel University, Philadelphia, USAMin Song - Department of Library and Information Science, Yonsei University, Seoul, Republic of Korea
- Publication Details
- Journal of informetrics, v 14(1), 100999
- Publisher
- Elsevier
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Information Science
- Web of Science ID
- WOS:000528948000004
- Scopus ID
- 2-s2.0-85077813973
- Other Identifier
- 991014976810104721
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- Collaboration types
- Domestic collaboration
- International collaboration
- Web of Science research areas
- Computer Science, Interdisciplinary Applications
- Information Science & Library Science