A5045750184- Genomics and Phylogenetic Studies
- Molecular Biology Techniques and Applications
- Anomaly Detection Techniques and Applications
- Bacterial Identification and Susceptibility Testing
- Advanced Data Processing Techniques
- RNA and protein synthesis mechanisms
- Antibiotic Resistance in Bacteria
- Machine Learning in Bioinformatics
- Machine Learning and Data Classification
- Bacteriophages and microbial interactions
- Metabolomics and Mass Spectrometry Studies
Technical University of Denmark
2020-2024
WGS-based antimicrobial susceptibility testing (AST) is as reliable phenotypic AST for several antimicrobial/bacterial species combinations. However, routine use of hindered by the need bioinformatics skills and knowledge resistance (AMR) determinants to operate vast majority tools developed date. By leveraging on ResFinder PointFinder, two freely accessible that can also assist users without skills, we aimed at increasing their speed providing an easily interpretable antibiogram output.The...
Antimicrobial resistance (AMR) is one of the most important health threats globally. The ability to accurately identify resistant bacterial isolates and individual antimicrobial genes (ARGs) essential for understanding evolution emergence AMR provide appropriate treatment. rapid developments in next-generation sequencing technologies have made this technology available researchers microbiologists at routine laboratories around world. However, tools those with limited experience...
ABSTRACT Infectious diseases continue to be a leading cause of mortality and pose significant global health threat. Thus the development tools for surveillance early detection emerging pathogens is needed. In this study, we introduce PathogenFinder2, novel predictor bacterial pathogenic capacity in humans, available through an online server ( http://genepi.food.dtu.dk/pathogenfinder2 ), or as standalone program https://github.com/genomicepidemiology/PathogenFinder2 ). The model, using...
The use of deep learning models in computational biology has increased massively recent years, and it is expected to continue with the current advances fields such as Natural Language Processing. These models, although able draw complex relations between input target, are also inclined learn noisy deviations from pool data used during their development. In order assess performance on unseen (their capacity
The use of deep learning models in computational biology has increased massively recent years, and it is expected to continue with the current advances fields such as Natural Language Processing. These models, although able draw complex relations between input target, are also inclined learn noisy deviations from pool data used during their development. In order assess performance on unseen (their capacity generalize), common split available randomly into development (train/validation) test...
Here, we present an automated pipeline for Download Of NCBI Entries (DONE) and continuous updating of a local sequence database based on user-specified queries. The can be created with either protein or nucleotide sequences containing all entries complete genomes only. automatically clean the by removing matches to contaminants. default contamination include from UniVec plasmids, marker genes sequencing adapters NCBI, E.coli genome, rRNA sequences, vectors satellite sequences. Furthermore,...