Genomic Data Analysis: DNA Microarray Basics and Applications

Genomic data is transforming modern medicine and biology, but understanding how to process and interpret this vast amount of information can feel overwhelming. This text-based course guides you through the foundational concepts of genomics and DNA microarray analysis. You will transition from a beginner to a confident analyst capable of understanding how microarrays work, processing raw genomic data, and identifying differentially expressed genes using modern bioinformatics workflows. What you'll learn: 1. Understand the fundamental biology of gene expression and the mechanics of DNA microarray technology. 2. Explore the workflow of genomic data generation, from sample preparation to hybridization. 3. Analyze microarray datasets using modern R and Bioconductor packages. 4. Apply normalization and quality control techniques to ensure reliable genomic data. 5. Identify differentially expressed genes and interpret their biological significance. 6. Access and utilize public genomic repositories like the Gene Expression Omnibus. The course starts with essential terminology and the biological foundations of genomics before moving into data preprocessing, normalization, and statistical analysis. You will read through clear, step-by-step written explanations and practical data analysis walkthroughs. This course is designed for beginners in bioinformatics, biology students, and data science enthusiasts with no prior experience in genomics. Start your journey into genomics and unlock the secrets hidden within gene expression data today.