Competence of medicinal plant database using data mining algorithms for large biological databases. (December 2022)

• Record Type: Journal Article
• Authors: Krishnamoorthy, M.; Karthikeyan, R.
• Is Part Of: Measurement. Volume 24(2022)
• Publication Date: 2022-12
• Subjects: Biological databases -- Data mining -- Data analysis -- Competence algorithm; Detectors -- Periodicals; Measurement -- Periodicals; 530.7
• DOI: 10.1016/j.measen.2022.100420
• Languages: English
• ISSNs: 2665-9174

Abstract

Abstract: This article covers how to use algorithms to extract the most important information from huge biological data sets for various data mining needs. Bioinformatics newline refers to the application of computer techniques to analyse and interpret massive data sets. Bioinformatics has advanced dramatically in recent years as a result of the massive increase of biological data created by the scientific community. Data mining is an interdisciplinary field that aids in comprehending and analysing large amounts of data in order to generate useful information. There are various data mining activities that may be applied on big biological data sets, such as association rule mining, classification prediction clustering, and so on. Pattern matching and the use of fuzzy logic in data mining are two examples of related data mining jobs. The major goal of this study is to determine how well different data mining methods perform on huge biological data sets. The author's goal is to determine the efficacy of these algorithms on biological data, as well as to propose appropriate algorithms for a variety of biological data sets relevant to various disorders Newline.