Modern biology generates vast volumes of genetic data, making computational algorithms essential for uncovering biological insights. This written course provides a clear, accessible entry point into algorithmic biology and bioinformatics, breaking down complex computational concepts into digestible explanations.
By reading through core theories and studying algorithmic approaches, you will develop the foundational skills needed to analyze biological sequences, understand genome reconstruction, and explore current open challenges in computational genomics.
What you'll learn:
- Understand fundamental biological terminology and computational problem formulations in genomics
- Apply exact and heuristic sequence alignment algorithms to compare DNA and protein sequences
- Explore graph-based approaches and de Bruijn graphs used in modern genome assembly
- Analyze phylogenetic trees and evolutionary distance models using computational techniques
- Examine modern sequencing data processing workflows and quality control standards
- Study open challenges in structural bioinformatics and high-throughput biological data analysis
The course begins with foundational definitions and biological string algorithms before advancing to structural and evolutionary modeling. It is designed for beginners in bioinformatics, computer science students curious about biology, and life science practitioners seeking a solid grounding in algorithmic thinking. Start reading today to build a strong theoretical foundation in algorithmic biology.
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