Pclust: protein network visualization highlighting experimental data

被引:6
|
作者
Li, Wenlin [1 ]
Kinch, Lisa N. [2 ]
Grishin, Nick V. [1 ,2 ]
机构
[1] Univ Texas SW Med Ctr Dallas, Dept Biophys & Biochem, Dallas, TX 75390 USA
[2] Univ Texas SW Med Ctr Dallas, Howard Hughes Med Inst, Dallas, TX 75390 USA
基金
美国国家卫生研究院;
关键词
SIMILARITY NETWORKS; GENERATION; PREDICTION; SEQUENCE;
D O I
10.1093/bioinformatics/btt451
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
One approach to infer functions of new proteins from their homologs utilizes visualization of an all-against-all pairwise similarity network (A2ApsN) that exploits the speed of BLAST and avoids the complexity of multiple sequence alignment. However, identifying functions of the protein clusters in A2ApsN is never trivial, due to a lack of linking characterized proteins to their relevant information in current software packages. Given the database errors introduced by automatic annotation transfer, functional deduction should be made from proteins with experimental studies, i.e. 'reference proteins'. Here, we present a web server, termed Pclust, which provides a user-friendly interface to visualize the A2ApsN, placing emphasis on such 'reference proteins' and providing access to their full information in source databases, e. g. articles in PubMed. The identification of 'reference proteins' and the ease of cross-database linkage will facilitate understanding the functions of protein clusters in the network, thus promoting interpretation of proteins of interest.
引用
收藏
页码:2647 / 2648
页数:2
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