Abstract
The advancement in the field of literature search and automatic detection of pointers between biologically relevant entities with their corresponding records in articles and annotation databases is largely due to the increasing interest in the development of biomedical text mining. The continuous growth is happening in biomedical sciences which include scientific articles, patents, patient records, database textual descriptions. With the practical relevance of these resources for the design, interpretation and evaluation of bioinformatics and experimental research resulted in the implementation of a considerable number of new applications. This chapter discusses the introduction to text mining and its implementation. Further, it is extended with few case studies of text mining using different approaches.
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Moharir, M., Maiya, P. (2020). Text Mining in Bioinformatics. In: Srinivasa, K., Siddesh, G., Manisekhar, S. (eds) Statistical Modelling and Machine Learning Principles for Bioinformatics Techniques, Tools, and Applications. Algorithms for Intelligent Systems. Springer, Singapore. https://doi.org/10.1007/978-981-15-2445-5_5
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DOI: https://doi.org/10.1007/978-981-15-2445-5_5
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