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Biotechnology · Moderate · Live online

Antibiotic Resistance Genomics: WGS, Bioinformatics & Resistance Gene Characterization

Hands-On Training in Bacterial Whole-Genome Sequencing, Antibiotic Resistance Gene Detection, Molecular Characterization & Comparative Resistome Analysis

12–14 Nov 20265:00 PM IST3 Days (60-90 MIn)Certificate

About This Course

Antimicrobial resistance (AMR) is a major global health challenge, creating an increasing need for advanced genomic surveillance and molecular characterization of antibiotic-resistant pathogens. Whole-genome sequencing (WGS) and bioinformatics enable researchers to identify antibiotic resistance genes (ARGs), investigate molecular resistance mechanisms, and analyze resistance profiles across bacterial isolates.

This 3-day hands-on workshop provides practical training in bacterial WGS data analysis, genome assembly, antibiotic resistance gene detection, functional annotation, and comparative resistome profiling. Participants will work with public genomic datasets using established bioinformatics tools, including Galaxy, FastQC, SPAdes, QUAST, NCBI AMRFinderPlus, CARD, and Python, to develop skills applicable to microbiology, biotechnology, and antimicrobial resistance research.

Aim

To develop practical knowledge and computational skills in bacterial whole-genome sequencing, antibiotic resistance gene identification, molecular characterization, and comparative resistome analysis using bioinformatics tools and genomic databases.

Workshop Objectives

  • Understand the molecular mechanisms and genetic basis of antibiotic resistance.
  • Explore bacterial whole-genome sequencing technologies and genomic databases.
  • Learn NGS data retrieval, quality assessment, and sequence preprocessing.
  • Understand bacterial genome assembly and genomic quality evaluation.
  • Identify and annotate antibiotic resistance genes using NCBI AMRFinderPlus and CARD.
  • Characterize resistance gene families, genetic variants, and associated molecular mechanisms.
  • Perform comparative resistome analysis across bacterial genomic datasets.
  • Apply Python-based tools for resistance gene visualization and genomic interpretation.
Next: Day-by-day →

Workshop Structure

Day 1: Bacterial Whole-Genome Sequencing, Data Quality Control & Genomic Profiling

Topics Covered:

  • Introduction to antimicrobial resistance (AMR) and its global research significance.
  • Molecular mechanisms of antibiotic resistance in bacterial pathogens.
  • Genetic basis of resistance: Acquired genes, point mutations and horizontal gene transfer.
  • Whole-genome sequencing (WGS) technologies: Illumina and Oxford Nanopore.
  • Applications of bacterial WGS in resistance genomics and microbial biotechnology.
  • Retrieval of bacterial genomic datasets from NCBI SRA and GenBank.
  • Understanding FASTQ, FASTA and paired-end sequencing data.
  • NGS quality assessment: Phred scores, GC content and sequencing errors.
  • Read trimming, adapter removal and quality filtering using fastp.
  • Bacterial species identification and sequencing contamination assessment.
  • Interpretation of sequencing quality reports using FastQC and MultiQC.

Hands-On 1: Bacterial WGS Data Retrieval & Quality Assessment

Retrieve a curated bacterial WGS dataset, perform read quality assessment and preprocessing using Galaxy, and generate a sequencing quality report.

Tools: NCBI SRA | Galaxy | FastQC | fastp | MultiQC


Day 2: Bacterial Genome Assembly, Antibiotic Resistance Gene Detection & Functional Annotation

Topics Covered:

  • Principles of bacterial genome assembly and genomic reconstruction.
  • De novo genome assembly using SPAdes.
  • Genome assembly evaluation: Contigs, N50, genome size and coverage.
  • Assessment of bacterial genome assembly quality using QUAST.
  • Introduction to antibiotic resistance genes (ARGs) and major resistance gene families.
  • Bioinformatics approaches for identifying acquired ARGs and resistance-associated mutations.
  • Antibiotic resistance gene detection using NCBI AMRFinderPlus.
  • Introduction to the Comprehensive Antibiotic Resistance Database (CARD).
  • Resistance gene identification and annotation using CARD Resistance Gene Identifier (RGI).
  • Classification of ARGs by antibiotic class and molecular resistance mechanism.
  • Interpretation of sequence identity, alignment coverage and gene detection confidence.

Hands-On 2: Antibiotic Resistance Gene Detection & Characterization

Analyze a curated bacterial genome assembly using NCBI AMRFinderPlus, identify resistance-associated genes, and characterize selected ARGs using CARD annotations.

Tools: Galaxy | SPAdes | QUAST | NCBI AMRFinderPlus | CARD/RGI


Day 3: Molecular Resistance Characterization, Comparative Resistome Analysis & Genomic Epidemiology

Topics Covered:

  • Molecular characterization of antibiotic resistance genes and genetic variants.
  • Functional annotation of ARGs and associated resistance mechanisms.
  • Classification of resistance determinants using the CARD Antibiotic Resistance Ontology.
  • Plasmid-associated resistance genes and horizontal gene transfer.
  • Introduction to bacterial resistomes and comparative resistome analysis.
  • Resistance gene distribution and profiling across bacterial isolates.
  • Antibiotic resistance gene presence–absence matrix generation.
  • Multilocus sequence typing (MLST) and bacterial strain characterization.
  • Introduction to genomic epidemiology and pathogen surveillance using NCBI Pathogen Detection.
  • Genotype–phenotype correlation using genomic predictions and antibiotic susceptibility testing (AST) data.
  • Python-based visualization of resistance gene distribution and comparative resistome profiles.
  • Scientific interpretation of genomic resistance patterns and prediction limitations.

Hands-On 3: Comparative Resistome Profiling & ARG Visualization

Analyze curated antibiotic resistance gene profiles from multiple bacterial isolates, generate an ARG presence–absence matrix, and visualize comparative resistome patterns through heatmaps using Python in Google Colab.

Tools: CARD | NCBI Pathogen Detection | Google Colab | Python (pandas, Matplotlib)

Who Should Enrol?

  • Undergraduate and Postgraduate Students: Biotechnology, Microbiology, Molecular Biology, Bioinformatics, Genetics, and Life Sciences.
  • PhD Scholars and Research Scholars: Working in antimicrobial resistance, bacterial genomics, molecular microbiology, and infectious disease research.
  • Academicians and Faculty Members: Teaching or conducting research in biotechnology, genomics, microbiology, and computational biology.
  • Microbiologists and Molecular Biologists: Interested in genomic approaches to antibiotic resistance detection and characterization.
  • Bioinformatics and Genomics Researchers: Seeking practical experience in WGS analysis, ARG identification, and comparative resistome profiling.
  • Clinical and Public Health Researchers: Working in infectious disease genomics, pathogen surveillance, and antimicrobial resistance research.
  • Biotechnology and Pharmaceutical Professionals: Interested in microbial genomics, resistance mechanisms, and computational sequence analysis.
Next: Dates →

Important Dates

Registration Ends

November 12, 2026
IST 4:30 PM

Workshop Dates

November 12, 2026 – November 14, 2026
IST 5:00 PM

Workshop Outcomes

 

  • Retrieve and analyze bacterial WGS datasets from public genomic repositories.
  • Perform sequencing quality control and interpret genome assembly metrics.
  • Identify antibiotic resistance genes using established bioinformatics workflows.
  • Characterize resistance determinants based on gene families, antibiotic classes, and molecular mechanisms.
  • Compare antibiotic resistance gene profiles across bacterial isolates.
  • Generate ARG presence–absence matrices and comparative resistome heatmaps.
  • Interpret genomic resistance predictions and recognize their limitations in determining antibiotic susceptibility.
  • Apply acquired bioinformatics skills to AMR genomics and microbiology research projects.
Next: Fees →

Fee Structure

Student Fee

₹2,499 | $65

Enrol as Student

Ph.D. Scholar / Researcher Fee

₹3,499 | $75

Enrol as Ph.D. Scholar / Researcher

Academician / Faculty Fee

₹4,499 | $85

Enrol as Academician / Faculty

Industry Professional Fee

₹5,499 | $105

Enrol as Industry Professional

Next: FAQ →

Frequently asked questions

Will I get the recording?

Yes. Paid participants get the session recordings and study material in their NanoSchool dashboard (My registrations → Recorded Lectures / Study Material).

What if I miss a live session?

Watch the recording in your dashboard and send your questions to the mentor through the support desk.

Do I get a certificate?

Yes, an e-certificate of participation after the workshop, with a QR code anyone can verify and an "Add to LinkedIn" button.

Which fee category applies to me?

Choose the category that matches your current role: Student, Ph.D. Scholar / Researcher, Academician / Faculty or Industry Professional.

How can I pay?

By card, UPI or PayPal on the payment page; international bank transfer is also available there.

What is the refund policy?

See our Returns, Refunds & Cancellation policy: Returns, Refunds & Cancellation policy

Need Help?

We’re here for you!


(+91) 120-4781-217
WhatsApp +91 99581 61117

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