There is growing awareness of the need for mathematics and computing to quantitatively understand the complex dynamics and feedbacks in the life sciences. Although several institutions and research groups are conducting pioneering multidisciplinary research, communication and education across fields remains a bottleneck. The opportunity is ripe for using education research-supported mechanisms of cross-disciplinary training at the intersection of mathematics, computation and biology. This case study uses the computational apprenticeship theoretical framework to describe the efforts of a computational biology lab to rapidly prototype, test, and refine a mentorship infrastructure for undergraduate research experiences. We describe the challenges, benefits, and lessons learned, as well as the utility of the computational apprenticeship framework in supporting computational/math students learning and contributing to biology, and biologists in learning computational methods. We also explore implications for undergraduate classroom instruction, and cross-disciplinary scientific communication.

中文翻译：

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通过教育和软件基础架构支持计算学徒制。肿瘤数学研究实验室的案例研究

人们越来越认识到需要数学和计算来定量了解生命科学中的复杂动力学和反馈。尽管一些机构和研究小组正在进行开创性的多学科研究，但是跨领域的交流和教育仍然是瓶颈。在数学，计算和生物学的交汇处使用教育研究支持的跨学科培训机制的时机已经成熟。本案例研究使用计算学徒理论框架来描述计算生物学实验室为为本科生的研究经验快速原型设计，测试和完善指导基础设施而做出的努力。我们描述了挑战，收益和经验教训，以及计算学徒制框架在支持计算/数学学生学习和促进生物学以及生物学家学习计算方法方面的效用。我们还将探讨对本科课堂教学和跨学科科学交流的影响。