Whole genome sequencing-based classification of human-related Haemophilus species and detection of antimicrobial resistance genes.
Margo DiricksThomas A KohlNadja KädingVladislav LeshchinskiySusanne HauswaldtOmar Jiménez VázquezChristian UtpatelStefan NiemannJan RuppMatthias MerkerPublished in: Genome medicine (2022)
Our new classification database and algorithm have the potential to improve diagnosis and surveillance of Haemophilus spp. and can easily be coupled with other public genotyping and antimicrobial resistance databases. Our data also point towards a possible pathogenic role of H. haemolyticus strains, which needs to be further investigated.
Keyphrases
- antimicrobial resistance
- machine learning
- deep learning
- big data
- genome wide
- endothelial cells
- artificial intelligence
- public health
- escherichia coli
- healthcare
- adverse drug
- induced pluripotent stem cells
- electronic health record
- genetic diversity
- mental health
- high throughput
- pluripotent stem cells
- loop mediated isothermal amplification
- real time pcr
- human health
- label free
- gene expression
- drug induced
- neural network
- climate change
- genome wide analysis
- high resolution
- genome wide identification
- quantum dots