ZCURVE 3.0: identify prokaryotic genes with higher accuracy as well as automatically and accurately select essential genes

Zhi-Gang Hua; Yan Lin; Ya-Zhou Yuan; De-Chang Yang; Wen Wei; Feng-Biao Guo

doi:10.1093/nar/gkv491

ZCURVE 3.0: identify prokaryotic genes with higher accuracy as well as automatically and accurately select essential genes

Nucleic Acids Res. 2015 Jul 1;43(W1):W85-90. doi: 10.1093/nar/gkv491. Epub 2015 May 14.

Authors

Zhi-Gang Hua¹, Yan Lin², Ya-Zhou Yuan¹, De-Chang Yang¹, Wen Wei¹, Feng-Biao Guo³

Affiliations

¹ Center of Bioinformatics, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, China Center for Information in BioMedicine, University of Electronic Science and Technology of China, Chengdu 610054, China Health Big Data Science Research Center, Big Data Research Center, University of Electronic Science and Technology of China, Chengdu 610054, China Key Laboratory for NeuroInformation of the Ministry of Education, University of Electronic Science and Technology of China, Chengdu 610054, China.
² Department of Physics, Tianjin University, Tianjin 300072, China Key Laboratory of Systems Bioengineering, Ministry of Education, Tianjin 300072, China Collaborative Innovation Center of Chemical Science and Engineering, Tianjin 300072, China.
³ Center of Bioinformatics, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, China Center for Information in BioMedicine, University of Electronic Science and Technology of China, Chengdu 610054, China Health Big Data Science Research Center, Big Data Research Center, University of Electronic Science and Technology of China, Chengdu 610054, China Key Laboratory for NeuroInformation of the Ministry of Education, University of Electronic Science and Technology of China, Chengdu 610054, China fbguo@uestc.edu.cn.

Abstract

In 2003, we developed an ab initio program, ZCURVE 1.0, to find genes in bacterial and archaeal genomes. In this work, we present the updated version (i.e. ZCURVE 3.0). Using 422 prokaryotic genomes, the average accuracy was 93.7% with the updated version, compared with 88.7% with the original version. Such results also demonstrate that ZCURVE 3.0 is comparable with Glimmer 3.02 and may provide complementary predictions to it. In fact, the joint application of the two programs generated better results by correctly finding more annotated genes while also containing fewer false-positive predictions. As the exclusive function, ZCURVE 3.0 contains one post-processing program that can identify essential genes with high accuracy (generally >90%). We hope ZCURVE 3.0 will receive wide use with the web-based running mode. The updated ZCURVE can be freely accessed from http://cefg.uestc.edu.cn/zcurve/ or http://tubic.tju.edu.cn/zcurveb/ without any restrictions.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Algorithms
Genes, Archaeal*
Genes, Bacterial*
Genes, Essential
Genome, Archaeal
Genome, Bacterial
Internet
Software*