APPLICATIONS OF TECHNOLOGY:
- Identification of plasmids in assembled bacterial genomes
- Recovery of plasmids from assembled bacterial genomes without any prior taxonomical knowledge with a low false positive rate
- Plasmids are extrachromosomal genetic elements that are an important driver of DNA exchange and genetic innovation in prokaryotes. The success of plasmids has been attributed to their independent replication from host cell chromosomes and their frequent self-transfer. In recent years, the Department of Energy (DOE) has recognized the importance of plasmid DNA to the viability and success of microbial communities.
Researchers at Berkeley Lab have developed DelPlasmid, a novel software that helps identify plasmids in assembled bacterial genomes.
DelPlasmid is Long Short-Term Memory (LSTM)-based on a deep learning model that takes as input a combination of assembled sequences and extracted features to identify bacterial plasmids. This model was trained on high-quality plasmid sequences from the ACLAME database and the NCBI Refseq.microbial dataset. The tool achieved an AUC-ROC of 91% on a 5-fold cross-validation.
DEVELOPMENT STAGE: Proven principle
FOR MORE INFORMATION:
Andreopoulos, William, Balewski, Jan, and USDOE. DelPlasmid: Finding Plasmids with Deep Learning and Machine Learning v1. Computer software. https://www.osti.gov//servlets/purl/1818866. USDOE. 12 Aug. 2020. Web. doi:10.11578/dc.20210903.3.
OPPORTUNITIES: Available /Open Source
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