Detection of Protein Catalytic Sites in the Biomedical Literature
Detection of Protein Catalytic Sites in the Biomedical Literature
复制标题
生物医学文献中蛋白质催化位点的检测
DOI：
10.1142/9789814447973_0042
复制
发表时间：
2012
影响因子：
--
通讯作者：
M. Wall
中科院分区：
文献类型：
--
作者：
Karin M. Verspoor;Andrew D. MacKinlay;J. Cohn;M. Wall
本文探讨了文本挖掘的应用，在生物医学文献中检测蛋白质功能位点的问题，并特别考虑了在该文献中识别催化位点的任务。我们提供了强有力的证据，需要文本挖掘技术，解决残留水平的蛋白质功能注释，通过分析两个语料库的覆盖范围策划的数据源。我们还探讨了建立一个基于文本的分类识别蛋白质功能位点的可行性，确定了低覆盖率的策划数据源和潜在的模糊性的信息蛋白质功能位点的挑战，必须加以解决。然而，我们产生了一个简单的分类器，在我们的全文银语料库上首次尝试解决这个分类任务时，它达到了合理的69% F-分数。这项工作在蛋白质位点的功能意义的计算预测以及捕获这些信息的数据库的管理工作流程中具有应用。
This paper explores the application of text mining to the problem of detecting protein functional sites in the biomedical literature, and specifically considers the task of identifying catalytic sites in that literature. We provide strong evidence for the need for text mining techniques that address residue-level protein function annotation through an analysis of two corpora in terms of their coverage of curated data sources. We also explore the viability of building a text-based classifier for identifying protein functional sites, identifying the low coverage of curated data sources and the potential ambiguity of information about protein functional sites as challenges that must be addressed. Nevertheless we produce a simple classifier that achieves a reasonable ∼69% F-score on our full text silver corpus on the first attempt to address this classification task. The work has application in computational prediction of the functional significance of protein sites as well as in curation workflows for databases that capture this information.
影响因子：
14.9
作者：
通讯作者：
--