Department of Medicine, University of California San Diego, La Jolla, CA 92093, USA; Department of Bioengineering, University of California San Diego, La Jolla, CA 92093, USA.
Department of Medicine, University of California San Diego, La Jolla, CA 92093, USA.
Cell Syst. 2019 Apr 24;8(4):275-280. doi: 10.1016/j.cels.2019.03.013.
Biological networks can substantially boost power to identify disease genes in genome-wide association studies. To explore different network GWAS methods, we challenged students of a UC San Diego graduate level bioinformatics course, Network Biology and Biomedicine, to explore and improve such algorithms during a four-week-long classroom competition. Here, we report the many creative solutions and share our experiences in conducting classroom crowd science as both a research and pedagogical tool.
生物网络可以极大地提高在全基因组关联研究中识别疾病基因的能力。为了探索不同的网络 GWAS 方法，我们让加州大学圣地亚哥分校研究生生物信息学课程的学生在为期四周的课堂竞赛中探索和改进这些算法。在这里，我们报告了许多有创意的解决方案，并分享了我们在进行课堂众包科学作为研究和教学工具方面的经验。
