Bioinformatics approach to enhance the undergraduate biology students’ understanding of plant terpenoid

Risanti Dhaniaputri, Hadi Suwono, B. Lukiati
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Abstract

Plant metabolite compounds have been applied on plant cellular metabolism, produces organic and inorganic compounds, primary and secondary bioactive molecules, such as glucose, amino acids, fat acids, alkaloids, flavonoids, and terpenoids. Undergraduate biology students learn about the plant terpenoid assisted by bioinformatics to store, manage, and interpret the molecular information about these compounds. This research aims to observe the students’ understanding of terpenoid through implementing bioinformatics approach. Besides, to investigate how practice the bioinformatics technology in learning terpenoid may impact students' comprehension of plant metabolism domain and their acquisition of bioinformatics inquiry skills. Bioinformatics is a computational database that relies on digital repositories of molecular biology informations. Data analysis was in the form of quantitative and qualitative descriptive using module learning resources based on terpenoid research and assisted by bioinformatics. The results indicate that students’ comprehension of learning and understanding terpenoid has improved, identification and analysis processes of article reviews showed that students were able to discuss and interpret research finding in silico bioinformatics using molecular docking procedures. Assessment of bioinformatics skills showed that all undergraduate biology students could follow the direct instructions well, answer the questions, practice the dry-lab experimental, and formulate the conclusion correctly.
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用生物信息学方法提高生物系本科生对植物萜类化合物的认识
植物代谢化合物应用于植物细胞代谢,产生有机和无机化合物、初级和次级生物活性分子,如葡萄糖、氨基酸、脂肪酸、生物碱、黄酮类和萜类化合物。生物学本科生通过生物信息学来学习植物萜类化合物,以存储、管理和解释这些化合物的分子信息。本研究旨在通过生物信息学方法观察学生对萜类化合物的理解。此外,研究在学习萜类化合物时使用生物信息学技术会如何影响学生对植物代谢领域的理解和生物信息学探究技能的掌握。生物信息学是一种依赖于分子生物学信息数字资源库的计算数据库。数据分析采用定量和定性描述的形式,利用基于萜类化合物研究的模块学习资源,并在生物信息学的辅助下进行。结果表明,学生学习和理解萜类化合物的能力有所提高,文章评论的识别和分析过程表明,学生能够利用分子对接程序讨论和解释硅生物信息学的研究成果。对生物信息学技能的评估表明,所有生物系本科生都能很好地按照直接指导回答问题,进行干实验练习,并正确地提出结论。
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