ArticleDNA research : an international journal for rapid publication of reports on genes and genomes2011
An integrative method for identifying the over-annotated protein-coding genes in microbial genomes.
Article in DNA research : an international journal for rapid publication of reports on genes and genomes, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Translatomics combined with transcriptomics and proteomics reveals novel functional, recently evolved orphan genes in Escherichia coli O157:H7 (EHEC).BMC genomics · 2016Article
- SearchDOGS bacteria, software that provides automated identification of potentially missed genes in annotated bacterial genomes.Journal of bacteriology · 2014Article
- Recognition of Protein-coding Genes Based on Z-curve Algorithms.Current genomics · 2014Article
- eCAMBer: efficient support for large-scale comparative analysis of multiple bacterial strains.BMC bioinformatics · 2014Article
- Article
- Re-annotation of protein-coding genes in 10 complete genomes of Neisseriaceae family by combining similarity-based and composition-based methods.DNA research : an international journal for rapid publication of reports on genes and genomes · 2013Article
- ORFcor: identifying and accommodating ORF prediction inconsistencies for phylogenetic analysis.PloS one · 2013Article
- Article
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Authors and funding
6 authors.
Funding
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Abstract
The falsely annotated protein-coding genes have been deemed one of the major causes accounting for the annotating errors in public databases. Although many filtering approaches have been designed for the over-annotated protein-coding genes, some are questionable due to the resultant increase in false negative. Furthermore, there is no webserver or software specifically devised for the problem of over-annotation. In this study, we propose an integrative algorithm for detecting the over-annotated protein-coding genes in microorganisms. Overall, an average accuracy of 99.94% is achieved over 61 microbial genomes. The extremely high accuracy indicates that the presented algorithm is efficient to differentiate the protein-coding genes from the non-coding open reading frames. Abundant analyses show that the predicting results are reliable and the integrative algorithm is robust and convenient. Our analysis also indicates that the over-annotated protein-coding genes can cause the false positive of horizontal gene transfers detection. The webserver of the proposed algorithm can be freely accessible from www.cbi.seu.edu.cn/RPGM.
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