Algorithms of DNA Sequencing in Python (Ongoing project)

This repository contains a collection of scripts, functions, and exercises developed during my progress through the Genomic Data Science Specialization and the Bioinformatics I Honours Track Certification. The goal of this work is to build practical proficiency in implementing and debugging genomic algorithms used in computational biology.

Aim

To gain hands-on experience with core algorithmic techniques in bioinformatics, including sequence analysis, pattern matching, and motif discovery, as part of a structured genomics specialization program.

Skills and Algorithms Covered

Hamming Distance computation for DNA sequence comparison

k-mer Clump Finding to locate high-frequency regions (e.g., origins of replication)

Boyer-Moore Pattern Matching Algorithm for efficient string search

Motif Detection using the MEME Suite

Use of BioPython for parsing and analyzing biological data

Coursework & Certification

Completed 10 coding-intensive modules in the Genomic Data Science track

Earned the Bioinformatics I Honors Track Certificate, demonstrating mastery of both theory and applied coding tasks

Tools & Libraries

Python (3.10+)

BioPython

MEME Suite

Jupyter Notebook (for stepwise development)

Next Steps

Extend repository with dynamic programming algorithms (e.g., global/local alignment)

Implement basic genome assembly techniques (e.g., De Bruijn graphs)

Apply algorithms to real sequencing datasets (FASTQ/FASTA) using BioPython pipelines.