Learn Antimicrobial Resistance Detection (AMR) Analysis using Linux
About Course
Antimicrobial resistance (AMR) is one of the most critical challenges in modern medicine and bioinformatics provides the tools to detect, analyze, and predict resistance directly from genomic data.
In this hands-on course, you’ll learn how to build complete AMR analysis pipelines starting from raw sequencing reads all the way to machine learning-based resistance prediction.
You’ll begin with the fundamentals of AMR and bioinformatics, then move on to Linux essentials, data preprocessing, and genome assembly using tools like SPAdes and Quast. Next, you’ll perform genome annotation with Prokka and detect resistance genes through ABRicate using multiple AMR databases (CARD, NCBI, ResFinder).
Finally, you’ll learn how to extract key features from AMR data, build an AMR gene presence–absence matrix, and apply machine learning models in Python to predict resistance patterns.
This course combines real-world genomic data, practical coding, and clear explanations to help you master AMR genomics analysis even if you’re a beginner.
No coding is required: all pipelines and codes are provided! Just follow the guided workflow and focus on learning the biological insights.
By the end of this course, you will:
-
Understand the principles of antimicrobial resistance genomics
-
Perform quality control and genome assembly using Linux-based tools
-
Annotate genomes and detect AMR genes using Prokka and ABRicate
-
Utilize major AMR databases for gene identification
-
Prepare AMR gene presence–absence data for ML analysis
-
Apply machine learning models to predict resistance patterns
-
Use fully provided codes and pipelines without manual scripting
Ideal For:
-
Students and researchers in bioinformatics, genomics, and microbiology
-
Beginners who want a guided, no-coding approach to AMR analysis
-
Professionals seeking hands-on AMR detection pipelines for real data
-
Anyone curious about integrating bioinformatics and machine learning
Enroll now and start your journey to master AMR genomics and machine learning powered resistance detection today!
Course Content
Introduction
-
What is Antimicrobial Resistance (AMR)?
15:41 -
Bioinformatics in AMR Research
20:03 -
Overview of the Course Pipelines
25:44 -
Setting Up Your Environment and Downloading Raw Data
29:53 -
Assignment 1: Install Tools and Run a Simple Bash Script Test
Basic Linux For Bioinformatics (Optional)
Data Preparation and Quality Control
Genome Assembly
Genome Annotation
AMR Gene Detection and Analysis
Advanced Machine Learning Models and Interpretation for AMR Genes
Student Ratings & Reviews
Your Instructor
Abdul Rehman Ikram
Bioinformatician | Data Analyst | Computational BiologistAbdul is a distinguished bioinformatician, data analyst, and computational biologist known for his exceptional contributions to the field of biomedical research. With a passion for integrating technology and biology, Abdul has carved a niche for himself, leveraging cutting-edge computational techniques to unravel complex biological data.
Driven by a curiosity to decode the complexities of life, Abdul believes in the power of interdisciplinary approaches. He is committed to mentoring the next generation of scientists, fostering a culture of innovation and continuous learning.
