The UC Berkeley/UCSF Graduate Program in Bioengineering, Berkeley, California, United States.
Anal Chem. 2013 Aug 20;85(16):7622-8. doi: 10.1021/ac4010887. Epub 2013 Aug 7.
Perhaps paradoxically, we argue that the biological sciences are "data-limited". In contrast to the glut of DNA sequencing data available, high-throughput protein analysis is expensive and largely inaccessible. Hence, we posit that access to robust protein-level data is inadequate. Here, we use the framework of the formal engineering design process to both identify and understand the problems facing measurement science in the 21st century. In particular, discussion centers on the notable challenge of realizing protein analyses that are as effective (and transformative) as genomics tools. This Perspective looks through the lens of a case study on protein biomarker validation and verification, to highlight the importance of iterative design in realizing significant advances over currently available measurement capabilities in the candidate or targeted proteomics space. The Perspective follows a podium presentation given by the author at The 16th International Conference on Miniaturized Systems for Chemistry and Life Sciences (μTAS 2012), specifically focusing on novel targeted proteomic measurement tools based in microfluidic design. The role of unmet needs identification, iteration in concept generation and development, and the existing gap in rapid prototyping tools for separations are all discussed.
或许具有讽刺意味的是,我们认为生物科学是“数据受限的”。与大量可用的 DNA 测序数据相比,高通量蛋白质分析既昂贵又难以广泛获取。因此,我们假设获取稳健的蛋白质水平数据是不充分的。在这里,我们使用正式的工程设计过程框架来识别和理解 21 世纪测量科学面临的问题。特别是,讨论集中在实现与基因组学工具一样有效(和变革性)的蛋白质分析方面的显著挑战。本观点通过对蛋白质生物标志物验证和确认的案例研究来看待问题,突出了迭代设计在实现候选物或靶向蛋白质组学领域现有测量能力的显著进展方面的重要性。本观点紧随作者在第 16 届微型系统化学与生命科学国际会议(μTAS 2012)上的演讲,特别关注基于微流控设计的新型靶向蛋白质组学测量工具。讨论了未满足需求的识别、概念生成和开发中的迭代以及用于分离的快速原型工具中存在的差距。