计算机科学
基因组
抗菌肽
R包
计算生物学
特征(语言学)
数据挖掘
基因
生物
抗菌剂
计算科学
语言学
生物化学
微生物学
哲学
作者
Legana C H W Fingerhut,David J. Miller,Jan M. Strugnell,Norelle L. Daly,Ira Cooke
出处
期刊:Bioinformatics
[Oxford University Press]
日期:2020-07-14
卷期号:36 (21): 5262-5263
被引量:77
标识
DOI:10.1093/bioinformatics/btaa653
摘要
SUMMARY: Antimicrobial peptides (AMPs) are the key components of the innate immune system that protect against pathogens, regulate the microbiome and are promising targets for pharmaceutical research. Computational tools based on machine learning have the potential to aid discovery of genes encoding novel AMPs but existing approaches are not designed for genome-wide scans. To facilitate such genome-wide discovery of AMPs we developed a fast and accurate AMP classification framework, ampir. ampir is designed for high throughput, integrates well with existing bioinformatics pipelines, and has much higher classification accuracy than existing methods when applied to whole genome data. AVAILABILITY AND IMPLEMENTATION: ampir is implemented primarily in R with core feature calculation methods written in C++. Release versions are available via CRAN and work on all major operating systems. The development version is maintained at https://github.com/legana/ampir. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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