一种描述和分析批量生物注释质量的方法--基于UniProtKB的实例研究
An approach to describing and analysing bulk biological annotation quality: a case study using UniProtKB
摘要：
动机：注释是许多生物数据库的关键特征，用于向读者传达我们对序列的了解。理想情况下，注释是手动管理的，但手动管理成本高，耗时，需要专业知识和培训。考虑到这些问题和数据的指数增长，许多数据库实现了自动注释管道，以避免未注释的条目。手动和自动注释在数据库和注释器之间的质量各不相同，这使得用户对注释可靠性的评估成为问题。社区缺乏一个通用的度量标准来确定注释的质量和正确性，我们将在本文中讨论这个问题。具体来说，我们调查大量文本注释中的字重用，并将其与Zipf的最小努力原则。我们使用UniProt知识库（UniProtKB）作为案例研究来演示这种方法，因为它允许我们比较注释的变化，无论是随着时间的推移，自动和手动策划的注释之间。结果如下：通过将幂律分布应用于注释中的单词重用，我们在UniProtKB中显示出随着时间的推移的明显趋势，这与现有的自由文本英语质量研究一致。此外，我们显示了手动和自动化分析之间的明显区别，并随着蛋白质记录的成熟而研究它们。这些结果表明，这种方法具有独特的承诺，作为一种机制，判断注释质量。可用性：源代码可在作者的网站上获得：http://homepages.cs.ncl.ac.uk/m.j.bell1/annotation。联系人：phillip. newcastle.ac.uk
英文摘要：
Motivation: Annotations are a key feature of many biological databases, used to convey our knowledge of a sequence to the reader. Ideally, annotations are curated manually, however manual curation is costly, time consuming and requires expert knowledge and training. Given these issues and the exponential increase of data, many databases implement automated annotation pipelines in an attempt to avoid un-annotated entries. Both manual and automated annotations vary in quality between databases and annotators, making assessment of annotation reliability problematic for users. The community lacks a generic measure for determining annotation quality and correctness, which we look at addressing within this article. Specifically we investigate word reuse within bulk textual annotations and relate this to Zipf's Principle of Least Effort. We use UniProt Knowledge Base (UniProtKB) as a case study to demonstrate this approach since it allows us to compare annotation change, both over time and between automated and manually curated annotations. Results: By applying power-law distributions to word reuse in annotation, we show clear trends in UniProtKB over time, which are consistent with existing studies of quality on free text English. Further, we show a clear distinction between manual and automated analysis and investigate cohorts of protein records as they mature. These results suggest that this approach holds distinct promise as a mechanism for judging annotation quality. Availability: Source code is available at the authors website: http://homepages.cs.ncl.ac.uk/m.j.bell1/annotation. Contact: phillip.lord@newcastle.ac.uk
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
