Document Type : Original Article
Authors
1 PhD, Department of Knowledge and Information Science, University of Isfahan, Isfahan, Iran
2 Corvinus University of Budapest
3 Knowledge and Information science
4 استاد گروه علم اطلاعات و دانش شناسی دانشگاه اصفهان
Abstract
An examination of the thematic process of the articles reveals the process of thematic growth and development of a scientific field over time. The knowledge map identifies concepts and connections between concepts in a scientific field, and by illustrating the internal structure of a scientific field, it will help users to quickly have a clear understanding of the structure of the field by observing the concepts, relations, and distances. In this study, an attempt was made to identify the main topics (core) considered by researchers and specialists in this field by examining the thematic process of articles in this field. Also, the relationships of these concepts should be drawn in the form of thematic maps and knowledge maps. The paper aimed to provide a clear picture of the thematic relationships of articles in the field of bioinformatics in the Clarivate database. The research is an applied type that was performed through co-word analysis and social network analysis techniques. The present research community compiled all kinds of bioinformatics articles that have been indexed in the Clarivate database during the years 1975-2018. The study articles were retrieved using a keyword-based search strategy, It was designed by using a combination of keywords and phrases suggested by experts in the field of bioinformatics. Data analysis and thematic mapping of articles were performed using Ravar PreMap, BibExcel, UciNet, and NetDraw software. Drawing thematic maps of articles showed that according to the centrality indicators, issues such as Proteomics, Microarray, MicroRNA, Genomics, Gene Expression, Computational Biology, and Database are among the main topics in this field. The findings also showed that based on the calculation of the lifespan of the presence of keywords compared to the first year of presence in the articles and the last year of presence in the articles, topics such as LNCRNA, Big Data, Differentially Expressed Genes, Osteosarcoma, Next-Generation Sequencing, RNA-SEQ, Protein-Protein Interaction Network, High-Throughput Sequencing, Metagenomics and ITRAQ were identified as emerging topics. Thematic maps drawn in this field can provide researchers with a suitable model for determining research policy.
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