Associating Gene Ontology Terms with Pfam Protein Domains

被引:2
作者
Alborzi, Seyed Ziaeddin [1 ,3 ]
Devignes, Marie-Dominique [2 ]
Ritchie, David W. [3 ]
机构
[1] Univ Lorraine, LORIA, UMR 7503, F-54506 Vandoeuvre Les Nancy, France
[2] CNRS, LORIA, UMR 7503, F-54506 Vandoeuvre Les Nancy, France
[3] Inria Nancy Grand Est, F-54600 Villers Les Nancy, France
来源
BIOINFORMATICS AND BIOMEDICAL ENGINEERING, IWBBIO 2017, PT II | 2017年 / 10209卷
关键词
Protein structure; Protein function; Gene Ontology; Content-based filtering;
D O I
10.1007/978-3-319-56154-7_13
中图分类号
R318 [生物医学工程];
学科分类号
0831 ;
摘要
With the growing number of three-dimensional protein structures in the protein data bank (PDB), there is a need to annotate these structures at the domain level in order to relate protein structure to protein function. Thanks to the SIFTS database, many PDB chains are now cross-referenced with Pfam domains and Gene ontology (GO) terms. However, these annotations do not include any explicit relationship between individual Pfam domains and GO terms. Therefore, creating a direct mapping between GO terms and Pfam domains will provide a new and more detailed level of protein structure annotation. This article presents a novel content-based filtering method called GODM that can automatically infer associations between GO terms and Pfam domains directly from existing GO-chain/Pfam-chain associations from the SIFTS database and GO-sequence/Pfam-sequence associations from the UniProt databases. Overall, GODM finds a total of 20,318 nonredundant GO-Pfam associations with a F-measure of 0.98 with respect to the InterPro database, which is treated here as a "Gold Standard". These associations could be used to annotate thousands of PDB chains or protein sequences for which their domain composition is known but which currently lack any GO annotation. The GODM database is publicly available at http://godm.loria.fr/.
引用
收藏
页码:127 / 138
页数:12
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