Hankey William, Zanghi Nicholas, Crow Mackenzie M, Dow Whitney H, Kratz Austin, Robinson Ashley M, Robinson Meaghan R, Segarra Verónica A
Department of Pathology, Duke Cancer Center, Duke University, Durham, NC, United States.
Department of Biology, High Point University, High Point, NC, United States.
Front Genet. 2020 Dec 16;11:573992. doi: 10.3389/fgene.2020.573992. eCollection 2020.
Undergraduate students in the biomedical sciences are often interested in future health-focused careers. This presents opportunities for instructors in genetics, molecular biology, and cancer biology to capture their attention using lab experiences built around clinically relevant data. As biomedical science in general becomes increasingly dependent on high-throughput data, well-established scientific databases such as The Cancer Genome Atlas (TCGA) have become publicly available tools for medically relevant inquiry. The best feature of this database is that it bridges the molecular features of cancer to human clinical outcomes-allowing students to see a direct connection between the molecular sciences and their future professions. We have developed and tested a learning module that leverages the power of TCGA datasets to engage students to use the data to generate and test hypotheses and to apply statistical tests to evaluate significance.
生物医学科学专业的本科生通常对未来以健康为重点的职业感兴趣。这为遗传学、分子生物学和癌症生物学领域的教师提供了机会，他们可以利用围绕临床相关数据构建的实验室体验来吸引学生的注意力。随着一般生物医学科学越来越依赖高通量数据，诸如癌症基因组图谱（TCGA）等成熟的科学数据库已成为医学相关研究的公开可用工具。该数据库的最大优点是它将癌症的分子特征与人类临床结果联系起来，使学生能够看到分子科学与其未来职业之间的直接联系。我们开发并测试了一个学习模块，该模块利用TCGA数据集的力量，促使学生使用这些数据来生成和检验假设，并应用统计测试来评估显著性。
