cover of episode PlasmidHunter: Accurate and fast prediction of plasmid sequences using gene content profile and machine learning

PlasmidHunter: Accurate and fast prediction of plasmid sequences using gene content profile and machine learning

2023/2/3
logo of podcast PaperPlayer biorxiv bioinformatics

PaperPlayer biorxiv bioinformatics

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Link to bioRxiv paper: http://biorxiv.org/cgi/content/short/2023.02.01.526640v1?rss=1

Authors: Tian, R., Imanian, B.

Abstract: Plasmids are extrachromosomal DNA found in microorganisms. They often carry beneficial genes that help bacteria adapt to harsh conditions, but they can also carry genes that make bacteria harmful to humans. Plasmids are also important tools in genetic engineering, gene therapy, and drug production. However, it can be difficult to identify plasmid sequences from chromosomal sequences in genomic and metagenomic data. Here, we have developed a new tool called PlasmidHunter, which uses machine learning to predict plasmid sequences based on gene content profile. PlasmidHunter achieved high accuracies (up to 96.7%) and fast speeds in benchmark tests, outperforming other existing tools.

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