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Bioinformatics Specialization Exercises 🎓🔬

Welcome to my repository for the Bioinformatics Specialization course on Coursera! 🚀 This is where I document my journey through the exciting world of bioinformatics, solving algorithmic challenges, and learning cutting-edge techniques in computational biology. Let's dive in! 🧬

🌟 Skills Gained

  • 🧬 Bioinformatics: Decoding the secrets of biological data.
  • 🤓 Algorithms: Mastering algorithms tailored for bioinformatics puzzles.
  • 🌲 Suffix Tree: Supercharging string matching and genome assembly.
  • 🌿 UPGMA (Unweighted Pair Group Method with Arithmetic Mean): Building phylogenetic trees like a pro.
  • 📜 Viterbi Algorithm: Cracking dynamic programming in hidden Markov models (HMMs).
  • 🐍 Python Programming: Crafting powerful scripts for bioinformatics tasks.
  • 🔍 Whole Genome Sequencing: Analyzing and interpreting genome sequencing data.

🗂️ Repository Structure

  • exercises/: 💡 Algorithm solutions from the course.
  • notes/: 📚 My personal notes on bioinformatics concepts.
  • scripts/: 🛠️ Python tools developed throughout the course.
  • datasets/: 📂 Sample datasets used for exercises and projects.
  • results/: 📝 Output files showcasing analysis results.

🛠️ How to Use

  1. Clone the repository: 
    git clone https://github.com/Danial-Ghofrani/Bioinformatics_coursera.git
cd bioinformatics-specialization
  2. Explore the folders to find exercises, notes, or scripts that interest you. 🕵️‍♂️
  3. Run Python scripts by navigating to their directories
  4. Tweak and experiment with the scripts to truly make the learning experience your own! 💻✨

✨ Course Highlights

  • 🔢 Implementing algorithms like Needleman-Wunsch, UPGMA, and Burrows-Wheeler Transform.
  • 🔗 Understanding biological sequence alignment and assembly.
  • 🧠 Gaining insights into computational biology challenges.
  • 🐍 Developing Python programs for practical bioinformatics applications.

📋 Prerequisites

  • 🧑‍💻 Basic knowledge of programming (preferably Python).
  • 🧬 Familiarity with molecular biology concepts.
  • 🧩 A love for problem-solving and algorithms.

🔧 Tools and Libraries

The following tools and libraries will help you navigate through the exercises:

  • Python (3.7+)
  • Libraries: numpy, pandas, matplotlib, biopython

Install the required libraries using:

pip install numpy pandas matplotlib biopython

📊 Progress Tracker

Course Status
🧬 Finding Hidden Messages in DNA (Bioinformatics I) 🔄 In Progress
🧩 Genome Sequencing (Bioinformatics II) 🕒 Not Started
🔬 Comparing Genes, Proteins, and Genomes (Bioinformatics III) 🕒 Not Started
🌿 Molecular Evolution (Bioinformatics IV) 🕒 Not Started
📊 Genomic Data Science and Clustering (Bioinformatics V) 🕒 Not Started
🧬 Finding Mutations in DNA and Proteins (Bioinformatics VI) 🕒 Not Started
🧠 Bioinformatics Capstone: Big Data in Biology 🕒 Not Started

🤝 Contributing

This repository is my personal learning space, but collaboration makes everything better! 🌟 Feel free to share your ideas or improvements by opening an issue or submitting a pull request. Let's grow together! 💪

🌟 Happy Learning and Coding! 🧬💻✨