Real-time recognition of infection threats during nanopore sequencing

The project focused on the analysis of core genome variability in a closely related microbial population using nanopore sequencing technology and convolutional neural network. The uniqueness of the proposal is based on real-time identification, processing and analysis of genetic variability directly from raw sequencing signals without the need of lossy decoding. Thanks to that the sequencing can be stopped as sufficient data are gathered, and the crucial epidemiologic information is available immediately.