Applications of Data Mining Techniques in Medicinal Plant Bioinformatics: Frameworks, Tools, and Challenges

Abstract

Globally, lot quantities of data exist in medical, industry and other related fields. An interested area of research in bioinformatics a case study in medicinal plants is the application and improvement of data mining techniques to solve biological problems involved. The quantity and variety of data in natural sciences enhanced quickly. Therefore, data abstraction, data manipulation and pattern discovery techniques are require in dealing with such large varieties of medicinal plants. Analyzing huge biological medicinal plants’ data sets requires making sense of the data by inferring structure or generalizations from the data. Integration among different sources of data is likewise of most important interest, as complex relations may happen. In this research paper, some basic concepts of bioinformatics, data mining and WEKA explorer tool are discussed. This research supports the development and validation of herbal treatments by comparing their efficacy with orthodox medicines that enhances decision making for herbal practitioners through structured databases and software tools that provide accurate treatment recommendations. Also it strengthens the integration of bioinformatics with herbal medicine by facilitating gene expression analysis, sequence interpretation, and knowledge discovery, ultimately promoting more efficient herbal drug development and application which is the main goal. Therefore, the area of application of data mining in the field of bioinformatics was clearly stated in this research and the current opportunities and challenges of data mining in medicinal plants bioinformatics are discussed as well.