Word association norms, mutual information, and lexicography
Computational Linguistics
Visualizing a discipline: an author co-citation analysis of information science, 1972–1995
Journal of the American Society for Information Science
The Journal of Machine Learning Research
Accurate methods for the statistics of surprise and coincidence
Computational Linguistics - Special issue on using large corpora: I
Journal of the American Society for Information Science and Technology
Dynamic hybrid clustering of bioinformatics by incorporating text mining and citation analysis
Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining
Journal of the American Society for Information Science and Technology
Design challenges and misconceptions in named entity recognition
CoNLL '09 Proceedings of the Thirteenth Conference on Computational Natural Language Learning
PageRank for ranking authors in co-citation networks
Journal of the American Society for Information Science and Technology
The structure and dynamics of cocitation clusters: A multiple-perspective cocitation analysis
Journal of the American Society for Information Science and Technology
Journal of the American Society for Information Science and Technology
The skewness of computer science
Information Processing and Management: an International Journal
References made and citations received by scientific articles
Journal of the American Society for Information Science and Technology
Medical Informatics and Bioinformatics: A Bibliometric Study
IEEE Transactions on Information Technology in Biomedicine
Citation characterization and impact normalization in bioinformatics journals
Journal of the American Society for Information Science and Technology
Hi-index | 0.00 |
Bioinformatics is a fast-growing, diverse research field that has recently gained much public attention. Even though there are several attempts to understand the field of bioinformatics by bibliometric analysis, the proposed approach in this paper is the first attempt at applying text mining techniques to a large set of full-text articles to detect the knowledge structure of the field. To this end, we use PubMed Central full-text articles for bibliometric analysis instead of relying on citation data provided in Web of Science. In particular, we develop text mining routines to build a custom-made citation database as a result of mining full-text. We present several interesting findings in this study. First, the majority of the papers published in the field of bioinformatics are not cited by others (63 % of papers received less than two citations). Second, there is a linear, consistent increase in the number of publications. Particularly year 2003 is the turning point in terms of publication growth. Third, most researches of bioinformatics are driven by USA-based institutes followed by European institutes. Fourth, the results of topic modeling and word co-occurrence analysis reveal that major topics focus more on biological aspects than on computational aspects of bioinformatics. However, the top 10 ranked articles identified by PageRank are more related to computational aspects. Fifth, visualization of author co-citation analysis indicates that researchers in molecular biology or genomics play a key role in connecting sub-disciplines of bioinformatics.