About Course

This course equips students with theoretical knowledge and practical skills for metagenomic analysis, from sample collection to data interpretation, using computational tools and pipelines for real-world problems in ecology, medicine, and biotechnology.

Course abbreviation: XXX

Instructor: Dr. Amira Metwaly

Postdoctoral Scientist, Chair of Nutrition and Immunology, Technical University Munich (TUM), Germany. Tutorials: Ms. Mariam Oweda

Workload: 12 lectures, 3 hours each. Total workload: 42 hours: 36 hours of lectures and tutorials and 6 hours of self study.

Entrance requirements: Basic knowledge of biology and computer science.

Used media: PowerPoint presentation

Objectives

  • Understand metagenomic sequencing technologies and data types
  • Perform metagenomic data processing, assembly, and annotation
  • Analyze microbial communities, diversity, functions, and interactions
  • Apply metagenomic methods to real-world problems in ecology, medicine, and biotechnology

Competences to be Developed

  • R scripting and relevant bioinformatics tools for metagenomic analysis
  • Metagenomic sequencing technologies and data types
  • Metagenomic data processing, assembly, and annotation
  • Microbial community analysis including diversity, function, and interaction studies
  • Developing and interpreting research projects and scientific manuscripts

Assessment

  • Complete a research project applying metagenomic analysis techniques
  • Submit project outcomes as a high-quality manuscript suitable for peer-review submission
  • Present, discuss, and scientifically review the project during the final lecture
Show More

What Will You Learn?

  • Understand metagenomic sequencing technologies and data types
  • Perform metagenomic data processing, assembly, and annotation
  • Analyze microbial communities, diversity, functions, and interactions
  • Apply metagenomic methods to real-world problems in ecology, medicine, and biotechnology
  • R scripting and relevant bioinformatics tools for metagenomic analysis
  • Metagenomic sequencing technologies and data types
  • Metagenomic data processing, assembly, and annotation
  • Microbial community analysis including diversity, function, and interaction studies

Course Content

Lecture 1: Introduction to Metagenomics

  • Introduction to Metagenomics
    00:00

Lecture 2: Experimental Design and Sample Collection

Lecture 3: Metagenomic Sequencing and Data Preprocessing

Lecture 4: Taxonomic Profiling and Microbial Diversity

Lecture 5: Functional Annotation in Metagenomics

Lecture 6: Metagenome Assembly and Binning

Lecture 7: Machine Learning Applications in Metagenomics

Lecture 8: Applications in Metagenomics: Antimicrobial Resistance (AMR)

Lecture 9: Applications in Metagenomics: Marine Microbial Ecology

Lecture 10: Disease and Health: Host-Microbe Interactions

Lecture 11: Research Projects

Lecture 12: Project Presentations and Closure

Student Ratings & Reviews

No Review Yet
No Review Yet