期刊文献+

基于序列与结构域相似性的蛋白质直系同源聚类研究 被引量:2

Clustering orthologs based on sequence and domain similarites
在线阅读 下载PDF
导出
摘要 目的探讨直系同源蛋白质聚类分析的方法,为高效、快速的直系同源蛋白质聚类分析研究提供有效帮助。方法基于蛋白质序列的相似性和结构域的相似性,提出一种直系同源蛋白质聚类方法,实现了直系同源蛋白质的快速、精确聚类。结果对人类、酵母、蠕虫、果蝇、拟南芥和斑马鱼等六种真核生物序列直系同源蛋白质的聚类分析,结果明显优于NCBI和TIGR的聚类结果。结论利用蛋白质序列的相似性和结构域的相似性,可以有效筛选出假的同源关系,进而显著提高直系同源蛋白聚类的精确性和紧密性。 [ Objective ] To investigate the methods of orthologs clustering analysis, and provide a notion for auto- matic and robust clustering analysis of orthologs. [Methods] Based on the similarities of sequences and domains, a method to cluster orthologs was presented, which could automatic cluster orthologs from multiple species. [ Results ] Analysis on six completely sequenced eukaryotic genomes showed that a significant improvement of our clustering results compared with those by NCBI and TIGR. [ Conclusion ] It suggests that using the similarities of sequences and domains can filter the false homology relationships and improve the accuracy and robustness of orthologs cluster- ing.
出处 《中国现代医学杂志》 CAS CSCD 北大核心 2012年第27期15-18,共4页 China Journal of Modern Medicine
关键词 结构域 同源直系 聚类 真核生物 domain orthologs clustering eukaryotic
  • 相关文献

参考文献13

  • 1GALPERIN MY, KOONIN EV. Who's your neighbor new computational approaches for functional genomics[J]. Nature. Biotechnology, 2000, 18(6): 609-613.
  • 2TEKAIA F, YERAMIAN E. SuperPartitions: detection and classification of orthologs[J]. Gene, 2012, 492(1): 199-211.
  • 3SALICHOS L, ROKAS A. Evaluating ortholog prediction algorithms in a yeast model clade [J]. PLoS One, 2011, 6(4): e18755.
  • 4GREENE LH, LEWIS TE, ADDOU S, et al. The CATH domain structure database: new protocols and classification levels give a more comprehensive resource for exploring evolution [J]. Nucleic Acids Research, 2008, 35: D291-D297.
  • 5SCHAFFER AA, ARAVIND L, MADDEN TL, et al. Improving the accuracy of PSI-BLAST protein database searches with composition-based statistics and other refinements [J]. Nucleic Acids Research, 2001, 29(14): 2994-3005.
  • 6KIM K, KIM W, KIM S. ReMark: an automatic program for clustering orthologs flexibly combining a Recursive and a Markov clustering algorithms[J]. Bioinformatics, 2011, 27(12): 1731-1733.
  • 7EDGAR RC, SJOLANDER K. COACH: profile-profile alignment of protein families using hidden Markov models[J]. Bioinformatics, 2004, 20(8): 1309-1318.
  • 8HARRIS MA. The Gene Ontology (GO) database and informatics resource[J]. Nucleic Acids Research, 2004, 32: D258-D261.
  • 9TATUSOV RL, FEDOROVA N D, JACKSON JD, et al. The COG database: an updated version includes eukaryotes [J]. BMC Bioinformatics, 2003, 11(4): 41.
  • 10LEE Y, SULTANA R, PERTEA G, et al. Cross-referencing eukaryotic genomes: TIGR Orthologous Gene Alignments (TOGA)[J]. Genome Research, 2002, 12(3): 493-502.

同被引文献29

引证文献2

二级引证文献9

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部