生物学杂志

生物学杂志 ›› 2022, Vol. 39 ›› Issue (1): 127-.doi: 10. 3969/ j. issn. 2095-1736. 2022. 01. 127

• 教学研究 • 上一篇    

立足方法学基点 培育生物信息学素养

  

  1. 1. 重庆师范大学生命科学学院, 重庆401331; 2. 重庆邮电大学生物信息学院, 重庆400065
  • 出版日期:2022-02-18 发布日期:2022-02-15
  • 作者简介:李勃,博士,副教授,研究方向为生物信息学与计算生物学,E-mail:libcell@cqnu.edu.cn
  • 基金资助:
    重庆市高等教育教学改革研究项目(编号203295); 重庆邮电大学教育教学改革项目(编号XJG20105); 重庆邮电大学“课程思政”试点示范课程项目(编号XKCSZ2031)

Using methodology as the keystone to foster bioinformatics literacy

  1. 1. College of Life Sciences, Chongqing Normal University, Chongqing 401331, China;
    2. College of Bioinformation, Chongqing University of Posts and Telecommunications, Chongqing 400065, China
  • Online:2022-02-18 Published:2022-02-15

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摘要： 以方法学为切入点,结合现代生命科学的发展与科研实践,运用试验-对照比较、距离与相似性、特征提取与特征选择、聚类分析、分类预测、数据整合再分析,以及数据库和在线工具等多个重要生物信息学策略或方法,帮助学生在较短的时间内学习和了解有别于传统实验生物学的计算思维与方法,加深学生对生物学交叉学科研究手段的理解。通过在生物学相关课程讲授过程中对生物信息学研究方法的引入,强化高校生物学相关专业学生的数理思维和交叉学科知识的运用能力,提升本科生的培养质量。

关键词: 生物信息学策略, 方法学, 学科交叉, 基因表达谱, 数据整合

Abstract: Taking methodology as the entry point and combining with the rapid development of modern life science and scientific research practice, several important bioinformatics strategies or approaches were summarized and refined, which included the ideas of experimental- control comparison, distance and similarity, feature selection and feature extraction, clustering analysis, classification and prediction, data integration and re-analysis, databases and web-based tools, and so on. These bioinformatics strategies are designed to help students learn and understand computational thinking and methods that are different from traditional experimental biology in a short period of time, and to deepen their understanding of interdisciplinary research approaches in biology. In a word, the introduction of bioinformatics research strategies or approaches in biology-related courses can strengthen the mathematical thinking and the ability to apply cross-disciplinary biology-related knowledge of students, improving the quality of undergraduate training.

Key words: bioinformatics strategy, methodology, interdisciplinary, gene expression profile, data integration

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