Udemy - Learn Amr Detection - From Raw Genomic Reads To Ml Prediction

Learn Amr Detection: From Raw Genomic Reads To Ml Prediction

https://WebToolTip.com

Published 10/2025
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz
Language: English | Size: 3.44 GB | Duration: 7h 23m

Build end-to-end AMR analysis pipelines on Linux identify resistance genes, and prepare data for advanced ML predictions

What you'll learn
Understand the fundamentals of Antimicrobial Resistance (AMR) and its biological significance.
Learn how bioinformatics tools and databases are applied in AMR research and genomic analysis.
Set up a Linux-based bioinformatics environment and efficiently navigate the Linux file system.
Perform data preprocessing and quality control using tools like FastQC and Fastp.
Conduct de novo bacterial genome assembly using SPAdes and assess assembly quality with Quast.
Annotate genomes using Prokka and interpret gene annotation results in the context of AMR research.
Detect antimicrobial resistance genes from multiple databases using ABRicate.
Integrate all steps into a complete AMR analysis pipeline from raw data to gene detection.
Generate an AMR gene presence–absence matrix and prepare data for downstream analysis using Python.
Build and interpret machine learning models to predict antimicrobial resistance patterns based on genomic data.

Requirements
No prior experience in bioinformatics or Linux is required, this course is designed to start from the basics.
A computer (Windows, macOS, or Linux) with stable internet access for software installation and dataset downloads.
Basic understanding of biology or genetics will be helpful but not mandatory.
Interest in genomic data analysis, antimicrobial resistance, or computational biology.
Willingness to learn through hands-on practice using real-world data and pipelines.
Familiarity with Python programming will be an advantage but is not required, all steps are explained in detail.