1.1 Integrative Multi-Omics Analysis

Overview of Course

If you’re curious about how genes, proteins, and metabolites interact and want to uncover deeper biological insights from complex datasets, this course is for you.

Integrative Multi-Omics Analysis involves combining data from various omics layers—like genomics, transcriptomics, proteomics, and metabolomics—to provide a comprehensive understanding of biological systems. You’ll learn how to preprocess, analyze, and interpret multi-omics data using bioinformatics tools and statistical approaches.

Skills you’ll need: Multi-Omics Data Integration, R/Python Programming, Systems Biology, Data Visualization, Statistical Modeling, Machine Learning, Transcriptomics, Proteomics, Metabolomics, Network Analysis

Completing this course will help you:

Who is the course for?

This course is ideal for life science students, bioinformaticians, and researchers aiming to go beyond single-omics analysis. It suits those with a basic understanding of molecular biology and programming, and who want to apply computational methods to complex biological problems in areas like disease research, drug discovery, and personalized medicine.

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Course 1.2

Custom Pipeline Development in Python & R

Custom Pipeline Development in Python & R teaches you how to design, code, and optimize bioinformatics pipelines tailored to specific research needs. You’ll learn to automate multi-step processes for tasks like sequence analysis, data cleaning, and reporting using powerful scripting and workflow management tools.

Custom Pipeline Development in Python & R

5 lessons - 4:11 hours

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Course 1.3

Reproducible Research with Workflow Managers

Reproducible Research with Workflow Managers teaches you how to structure and automate bioinformatics projects using tools like Snakemake, Nextflow, and CWL. You'll learn to organize code, manage dependencies, and build workflows that are sharable, scalable, and reproducible across systems.