HydrAMP: a deep generative model for antimicrobial peptide discovery
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Updated
Sep 19, 2024 - Jupyter Notebook
HydrAMP: a deep generative model for antimicrobial peptide discovery
MTB++ a software developed to predict antimicrobial resistance to 13 antibiotics and 3 families of antimicrobials.
Bioinformatics analysis used to determine reinfection and relapse tuberculosis using whole genome sequencing data.
Antimicrobial Resistance Test Interpretation Engine
An antimicrobial resistance (AMR) dashboard.
Python code to integrate results of tb-pipeline and provide an antibiogram, mutations and variants
A data specification for harmonizing One Health AMR pathogen genomics contextual data. The specification provides standardized (ontology-based) fields and terms which are implemented via a spreadsheet collection template, supported by field and reference guides as well as different curation and new term request SOPs.
AMR/VF LGT focused bacterial genomics analysis workflow
Parse multiple Antimicrobial Resistance Analysis Reports into a common data structure
Scans genome contigs against the ResFinder, PlasmidFinder, and PointFinder databases.
A standardized Python pipeline for comparative analysis of antibiotic resistance genes (ARGs) in bacterial genomes.
Bacterial Assembly and Antimicrobial Resistance Genes In NextFlow
👨💻🧬🤖 deep neural networks: 1Dconvolution experiments with kernel size and stride length
Conditional Variational Auto-Encoder for generation of synthetic data for Antimicrobial Resistance.
Data and code repository for study aiming to understand ESBL carriage in Blantyre, Malawi
Harmonization of AMR predictor tool outputs
Collection of planning documents, visualizations, and presentations for my dissertation research. "Investigating Multidrug Resistance in Escherichia coli with Phylogenetics and Machine Learning"
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