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The automatic annotation of bacterial genomes

2012; Oxford University Press; Volume: 14; Issue: 1 Linguagem: Inglês

10.1093/bib/bbs007

1477-4054

Emily J. Richardson, Mick Watson,

Machine Learning in Bioinformatics

With the development of ultra-high-throughput technologies, the cost of sequencing bacterial genomes has been vastly reduced. As more genomes are sequenced, less time can be spent manually annotating those genomes, resulting in an increased reliance on automatic annotation pipelines. However, automatic pipelines can produce inaccurate genome annotation and their results often require manual curation. Here, we discuss the automatic and manual annotation of bacterial genomes, identify common problems introduced by the current genome annotation process and suggests potential solutions.