Keeney Jonathon G, Gulzar Naila, Baker Jack B, Klempir Ondrej, Hannigan Geoffrey D, Bitton Danny A, Maritz Julia M, King Charles H S, Patel Janisha A, Duncan Paul, Mazumder Raja
Department of Biochemistry and Molecular Medicine, School of Medicine and Health Sciences, The George Washington University, Washington, DC, USA.
Department of Biochemistry and Molecular Medicine, School of Medicine and Health Sciences, The George Washington University, Washington, DC, USA.
Drug Discov Today. 2024 Mar;29(3):103884. doi: 10.1016/j.drudis.2024.103884. Epub 2024 Jan 12.
The volume of nucleic acid sequence data has exploded recently, amplifying the challenge of transforming data into meaningful information. Processing data can require an increasingly complex ecosystem of customized tools, which increases difficulty in communicating analyses in an understandable way yet is of sufficient detail to enable informed decisions or repeats. This can be of particular interest to institutions and companies communicating computations in a regulatory environment. BioCompute Objects (BCOs; an instance of pipeline documentation that conforms to the IEEE 2791-2020 standard) were developed as a standardized mechanism for analysis reporting. A suite of BCOs is presented, representing interconnected elements of a computation modeled after those that might be found in a regulatory submission but are shared publicly - in this case a pipeline designed to identify viral contaminants in biological manufacturing, such as for vaccines.
核酸序列数据量最近呈爆炸式增长，这加大了将数据转化为有意义信息的挑战。处理数据可能需要一个日益复杂的定制工具生态系统，这增加了以易于理解的方式传达分析结果的难度，同时还需要足够详细以便做出明智决策或进行重复操作。对于在监管环境中交流计算结果的机构和公司来说，这可能特别重要。生物计算对象（BCOs；一种符合IEEE 2791-2020标准的流程文档实例）被开发出来作为分析报告的标准化机制。本文展示了一组BCOs，它们代表了一个计算的相互关联元素，该计算是仿照监管申报中可能出现的元素建模的，但会公开共享——在这种情况下，是一个旨在识别生物制造（如疫苗生产）中病毒污染物的流程。
