Bioinformatic tools for microbiologists

08:30 • 1461 • AMR-Diag: neural network based genotype-to-phenotype prediction of resistance towards ß-lactams in <em>Escherichia coli</em> and <em>Klebsiella pneumoniae</em> > R. Rafi AHMAD (Hamar) 08:35 • 1532 • Bacterial typing via raw nanopore signals > M. Marketa NYKRYNOVA (Brno) 08:40 • 1624 • Genomic island prediction and comparison to investigate bacterial evolution and outbreaks > C. Claire BERTELLI (Lausanne) 08:45 • 1957 • MotilityJ: an open-source tool for the bacterial motility quantification > G. Gabriela CHICHÓN DE LA FUENTE (Logroño) 08:50 • 2292 • Benchmarking taxonomic classifiers with simulated nanopore-read profiles for clinical metagenomic diagnostics > K. Kumeren GOVENDER (Oxford) 08:55 • 3410 • Short-read metagenomic assembly: finding the best fit in a world of options > M. Mario RAMIREZ (Lisbon) 09:00 • 3462 • Defining the impact of coverage depth and choice of assembler in bacterial sequencing > N. Nikolaos STREPIS (Rotterdam) 09:05 • 3537 • Genome-wide mutation scoring for machine learning-based antimicrobial resistance prediction in <em>Pseudomonas aeruginosa</em> > S. Sarah LEPUSCHITZ (Vienna) 09:10 • 4080 • Combining targeted sequencing and machine learning to optimise antibiotic therapy in tuberculosis patients > S. Sebastian DÜMCKE (Schlieren) 09:15 • 4395 • PATO: a suite of bioinformatics tools for analysing pangenomes > M. Miguel D. FERNÁNDEZ-DE-BOBADILLA (Madrid) 09:20 • INT78 • Q&A/Discussion