Kumar Anuj
Department of Molecular, Cellular, and Developmental Biology, Life Sciences Institute, University of Michigan, Ann Arbor, MI 48109-2216, USA.
Cell Biol Educ. 2005 Winter;4(4):323-9. doi: 10.1187/cbe.04-12-0057.
With genomics well established in modern molecular biology, recent studies have sought to further the discipline by integrating complementary methodologies into a holistic depiction of the molecular mechanisms underpinning cell function. This genomic subdiscipline, loosely termed "systems biology," presents the biology educator with both opportunities and obstacles: The benefit of exposing students to this cutting-edge scientific methodology is manifest, yet how does one convey the breadth and advantage of systems biology while still engaging the student? Here, I describe an active-learning approach to the presentation of systems biology. In graduate classes at the University of Michigan, Ann Arbor, I divided students into small groups and asked each group to interpret a sample data set (e.g., microarray data, two-hybrid data, homology-search results) describing a hypothetical signaling pathway. Mimicking realistic experimental results, each data set revealed a portion of this pathway; however, students were only able to reconstruct the full pathway by integrating all data sets, thereby exemplifying the utility in a systems biology approach. Student response to this cooperative exercise was extremely positive. In total, this approach provides an effective introduction to systems biology appropriate for students at both the undergraduate and graduate levels.
随着基因组学在现代分子生物学中的确立,最近的研究试图通过将互补方法整合到对支撑细胞功能的分子机制的整体描述中来推动这一学科的发展。这个基因组学的子学科,被宽泛地称为“系统生物学”,给生物学教育工作者带来了机遇和挑战:让学生接触这种前沿科学方法的好处是显而易见的,然而,如何在吸引学生的同时传达系统生物学的广度和优势呢?在这里,我描述一种用于呈现系统生物学的主动学习方法。在密歇根大学安娜堡分校的研究生课程中,我将学生分成小组,要求每个小组解读一个描述假设信号通路的样本数据集(例如,微阵列数据、双杂交数据、同源性搜索结果)。每个数据集模仿现实的实验结果,揭示了该通路的一部分;然而,学生只有通过整合所有数据集才能重建完整的通路,从而例证了系统生物学方法的实用性。学生对这个合作练习的反应非常积极。总的来说,这种方法为本科生和研究生提供了对系统生物学的有效入门。