Promotech: a general tool for bacterial promoter recognition

被引:25
作者
Chevez-Guardado, Ruben [1 ]
Pena-Castillo, Lourdes [1 ,2 ]
机构
[1] Mem Univ Newfoundland, Dept Comp Sci, 230 Elizabeth Ave, St John, NF A1C 5S7, Canada
[2] Mem Univ Newfoundland, Dept Biol, 230 Elizabeth Ave, St John, NF A1C 5S7, Canada
基金
加拿大自然科学与工程研究理事会;
关键词
Bacterial promoter; Promoter recognition; Promoter prediction; Machine learning; Microbiology; Bioinformatics; POLYMERASE BINDING-SITE; NUCLEOTIDE-SEQUENCE; RNA-SEQ;
D O I
10.1186/s13059-021-02514-9
中图分类号
Q81 [生物工程学(生物技术)]; Q93 [微生物学];
学科分类号
071005 ; 0836 ; 090102 ; 100705 ;
摘要
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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收藏
页数:16
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