Mål for prosjektet
To use new technologies in combination with AI and ML to create a system that can detect and characterize resistant pathogens much faster ( < 5 hours rather than 2-4 days) than the current clinical methods. This would help to reduce the spread of antimicrobial resistance and can potentially save millions of human and animal lives in the long run.
Current methods for detecting resistant bacteria are time-consuming. This contributes to inappropriate use of antibiotics and the spread of AMR.
Project objectives
Use AI / ML combined with novel technologies to characterize pathogenic bacteria and their susceptibility profiles in less than 5 hours by:
- Development of novel algorithms for taxonomic characterization of sequencing data
- Investigating explainability of Deep Learning models for pathogen classification from quantitative phase microscopy (QPM) images
- Novel AI / ML model development for prediction of minimum inhibitory concentration (MIC) of antibiotics from bacterial whole genome sequencing (WGS) data
- Building models to investigate the national and regional burden of AMR
Results
All research results in the project are available from the CRISTIN project page.
Project News
MysteryMaster paper published in BMC Bioinformatics!
MysteryMaster - BMC Bioinformatics
Voyager reached 1500 downloads on bioconda!
Preprint available: Real-time Taxonomic Characterization of Long-read Mixed-species Sequencing Samples in Sorted Motif Distance Space: Voyager” - downloadable at Cristin
Software
Voyager: Tool for Real-time Taxonomic Characterization of Long-read Mixed-species Sequencing Samples in Sorted Motif Distance Space.
Language: C++ / Java
Install with bioconda
Repository Link
Watch a video of Voyager in action on Youtube here.
MysteryMaster: Graphical Oxford Nanopore read demultiplexer.
Language: C++ / Java
Install with bioconda
Repository Link
Mango: Unearthing Patterns in Large-Scale Biological Data Through Interactive Correlation Analysis.
Language: C++ / Java
K-MARVEL: K-Mer based Antimicrobial Resistance Virtual Exploration Lab.
Language: Rust
- rafi.ahmad@inn.no
- Phone
- +47 62 51 78 45
Associate Professor
- manfred.grabherr@inn.no
- Phone
- +47 61 28 80 07
PhD Candidate
PostDoc Resarcher
- jonathan.hira@inn.no
- Phone
- +47 62 51 72 80