The way in which computer code is perceived and used in biological research has been a source of some controversy and confusion, and has resulted in sub-optimal outcomes related to reproducibility, scalability and productivity. We suggest that the confusion is due in part to a misunderstanding of the function of code when applied to the life sciences. Code has many roles, and in this paper we present a three-dimensional taxonomy to classify those roles and map them specifically to the life sciences. We identify a “sweet spot” in the taxonomy—a convergence where bioinformaticians should concentrate their efforts in order to derive the most value from the time they spend using code. We suggest the use of the “inverse Conway maneuver” to shape a research team so as to allow dedicated software engineers to interface with researchers working in this “sweet spot.” We conclude that in order to address current issues in the use of software in life science research such as reproducibility and scalability, the field must reevaluate its relationship with software engineering, and adapt its research structures to overcome current issues in bioinformatics such as reproducibility, scalability and productivity.

在生物学研究中感知和使用计算机代码的方式一直是一些争议和困惑的根源，并导致了与可重复性、可扩展性和生产力相关的次优结果。我们认为，这种混乱部分是由于对代码应用于生命科学时的功能的误解造成的。代码有很多角色，在本文中，我们提出了一个三维分类法来对这些角色进行分类，并将它们专门映射到生命科学。我们确定了分类学中的一个“最佳点”——生物信息学家应该集中精力从他们使用代码的时间中获得最大价值的融合。我们建议使用“逆康威策略”来组建研究团队，以便让专门的软件工程师与在这个“最佳位置”工作的研究人员进行交流。我们的结论是，为了解决生命科学研究中软件使用的当前问题，例如再现性和可扩展性，该领域必须重新评估其与软件工程的关系，并调整其研究结构，以克服生物信息学中当前的问题，例如再现性、可扩展性和生产力。