Detection and Characterization of Antibiotic Resistance Genes (ARGs)
Decode Resistance. Analyze Genomes. Advance Public Health.
About This Course
This 3-day intensive workshop (1.5-hour lecture per day) provides a comprehensive introduction to the detection and characterization of antibiotic resistance genes (ARGs) using modern bioinformatics approaches. Participants will gain theoretical understanding and practical exposure to ARG databases, sequence quality control, computational detection methods, annotation strategies, abundance analysis, and visualization techniques. The workshop emphasizes hands-on learning and reproducible workflows suitable for academic research, clinical microbiology, and industry applications.
Aim
To provide participants with theoretical knowledge and hands-on bioinformatics skills to detect, analyze, and interpret antibiotic resistance genes (ARGs) from genomic and metagenomic datasets using widely adopted computational tools and databases.
Workshop Objectives
- To understand mechanisms of antimicrobial resistance and functional classes of ARGs
- To explore major ARG databases (CARD, ResFinder, ARG-ANNOT, NCBI AMR)
- To perform quality control and preprocessing of sequencing data
- To detect ARGs using BLAST, DIAMOND, HMMER, and RGI tools
- To annotate and quantify ARGs in genomes and metagenomes
- To characterize ARGs through phylogenetics, co-occurrence analysis, and visualization
- To generate reproducible ARG analysis reports suitable for research and publication
Workshop Structure
Day 1: Introduction to Antibiotic Resistance and ARGs
- Antimicrobial Resistance Overview: Mechanisms of resistance, clinical and environmental relevance
- ARGs: Types, functional classes, and common examples (β-lactamases, efflux pumps, aminoglycoside-modifying enzymes)
- Databases for ARGs: CARD, ResFinder, ARG-ANNOT, NCBI AMR database
- Sequence Data Preparation: Collecting bacterial genomes, metagenomic samples, and FASTA/FASTQ formats
- Quality Control: Read trimming, filtering, and assembly basics
- Tools: Python, Biopython, FASTQC, Trimmomatic
- Mini Task: Explore ARG databases and extract sequences for analysis
Day 2: Detection and Annotation of ARGs
- ARG Detection Approaches: BLAST-based, HMM-based, and machine learning approaches
- Functional Annotation: Mapping ARGs to resistance mechanisms, classes, and antibiotics
- Sequence Alignment and Similarity Search: BLAST, DIAMOND, and hidden Markov models (HMMs)
- ARG Abundance and Distribution Analysis: Quantification in genomes/metagenomes
- Tools: BLAST, DIAMOND, HMMER, CARD/RGI tool, Python (pandas, seaborn for visualization)
- Mini Task: Detect ARGs in a bacterial genome or metagenome dataset and generate resistance profiles
Day 3: Characterization, Visualization, and Reporting
- Characterization of ARGs: Phylogenetic context, mobile genetic elements, co-occurrence networks
- Predicting Phenotypic Resistance: Linking genotype to antibiotic susceptibility
- Visualization of ARG Distribution: Heatmaps, barplots, network diagrams
- Reproducibility & Reporting: Workflow documentation, figures for publication, interpretation of resistance patterns
- Tools: Python (pandas, matplotlib, seaborn, networkx), R (optional), CARD/RGI, NCBI tools
- Mini Task: Build a final ARG detection report with resistance profiles, distribution plots, and phylogenetic context
Who Should Enrol?
- Doctoral Scholars & Researchers: PhD candidates seeking to integrate computational workflows into their molecular research.
- Postdoctoral Fellows: Early-career scientists aiming to enhance their data-driven publication profile.
- University Faculty: Professors and HODs interested in modern bioinformatics pedagogy and tool mastery.
- Industry Scientists: R&D professionals from the Biotechnology and Pharmaceutical sectors transitioning to genomic-driven discovery.
- Postgraduate Students: Final-year PG students looking for specialized research-grade exposure beyond standard curricula.
Important Dates
Registration Ends
02/17/2026
IST 07:00 PM
Workshop Dates
02/17/2026 – 02/19/2026
IST 08:00 PM
Workshop Outcomes
By the end of this 3-day workshop (1.5-hour lecture per day), participants will be able to:
- Explain molecular mechanisms of antibiotic resistance
- Retrieve and curate ARG sequences from public databases
- Perform quality control and preprocessing of sequencing datasets
- Detect and annotate ARGs using computational approaches
- Analyze ARG abundance and distribution patterns
- Interpret genotype-to-phenotype resistance relationships
- Generate publication-ready visualizations and structured resistance reports
Fee Structure
Student Fee
₹1699 | $65
Ph.D. Scholar / Researcher Fee
₹2699 | $75
Academician / Faculty Fee
₹3699 | $85
Industry Professional Fee
₹4699 | $96
What You’ll Gain
- Live & recorded sessions
- e-Certificate upon completion
- Post-workshop query support
- Hands-on learning experience
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