期刊
GENOME BIOLOGY
卷 22, 期 1, 页码 -出版社
BMC
DOI: 10.1186/s13059-021-02514-9
关键词
Bacterial promoter; Promoter recognition; Promoter prediction; Machine learning; Microbiology; Bioinformatics
资金
- Natural Sciences and Engineering Research Council of Canada (NSERC) [RGPIN: 2019-05247]
- Memorial University (MUN)'s School of Graduate Studies
Promoters are genomic regions where transcription of specific genes is initiated, and Promotech is a machine-learning based method for recognizing promoters in various bacterial species. Promotech outperforms other prediction methods in terms of precision at the same level of recall.
Promoters are genomic regions where the transcription machinery binds to initiate the transcription of specific genes. Computational tools for identifying bacterial promoters have been around for decades. However, most of these tools were designed to recognize promoters in one or few bacterial species. Here, we present Promotech, a machine-learning-based method for promoter recognition in a wide range of bacterial species. We compare Promotech's performance with the performance of five other promoter prediction methods. Promotech outperforms these other programs in terms of area under the precision-recall curve (AUPRC) or precision at the same level of recall. Promotech is available at https://github.com/BioinformaticsLabAtMUN/PromoTech.
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