Python-Assignments-Bioinformatics 🧬

This repository contains assignments from the Introduction to Python course, specifically tailored for Bioinformatics in Health Sciences. Most scripts focus on the biological analysis of sequences, molecular weights, and data parsing.

Important

Note: These exercises are intended as a guide. Some scripts include personal modifications or scientific improvements (like water-loss calculations in proteins) that may differ from the basic assignment requirements. Always verify the code logic before use.

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Summary of Assignments

Foundational Python logic, including string manipulation, list comprehension, and basic dictionary usage for biological data.

• Assignment 1: Environment Setup
  • Introduction to the Python interpreter and basic variable assignments.
• Assignment 2: String Manipulation
  • Basic operations on DNA strings: counting nucleotides and finding simple motifs.
• Assignment 3: Lists & GC Content
  • Using lists to store sequence data and calculating the GC percentage of a DNA strand.
• Assignment 4: Dictionaries & Codons
  • Implementing dictionaries to map amino acids to their molecular weights and codons to residues.
• Assignment 5: Basic File Reading
  • Opening and reading simple text files containing single biological sequences.
• Assignment 6: Advanced FASTA Parsing
  • Developing logic to handle multi-line FASTA files and extracting headers from sequences.
• Assignment 7 (Object-Oriented Proteins): * Defines a Protein class to encapsulate identifiers and sequences.
  • Implements a custom FASTA Generator to handle large genomic files.
  • Calculates scientifically accurate Molecular Weight (accounting for water loss).
• Assignment 8 (Class Hierarchy & Inheritance): * Creates a Sequence superclass with specialized subclasses: DNASequence, RNASequence, and ProteinSequence.
  • Automates biological workflows: DNA ⮕ RNA (Transcription) and RNA ⮕ Protein (Translation).
  • Uses polymorphism to manage different molecular weight calculations across types.
• Assignment 9: Special Methods & Hashing
  • Implements "Special" methods (len, add, str, etc.) to make sequences behave like native Python objects.
  • Enables complex sorting based on Molecular Weight using comparison operators.
  • Implements hash to allow Sequence objects to be used as keys in dictionaries or stored in sets.
• Assignment 10: The Integrated Pipeline (Professional Tool)

  • Advanced CLI: Implements argparse for industry-standard command-line flags (-i, -o, -v).

  • Biological Precision: Unlike previous versions, this translation logic mimics real biology by searching for Start Codons and terminating at Stop Codons.

  • Performance Optimization: Uses Python sets for O(1) residue validation and Caching to store Molecular Weight results, preventing redundant calculations.

  • Robust Error Handling: Features a custom exception class IncorrectSequenceLetter to skip corrupt data without crashing the entire pipeline.

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Workflow Suggestions for Beginners

I am not an expert, but here are the suggestions I wish I had followed when I started:

• Editor: Download Visual Studio Code (VSC). It is extremely beginner-friendly and has a massive library of extensions.
  • Tip: Use the "vscode-pdf" extension to read assignment instructions side-by-side with your code.
• Environment: Install Python locally and link it to VSC. This makes managing scripts and libraries (like sys or math) much easier.
• Structure: Keep a sequence_dictionaries.py file in your root folder. It acts as a "central library" for your DNA tables and amino acid weights.
• Testing: Always test your scripts using the if __name__ == "__main__": block to ensure they run correctly from the terminal.

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Technical Stack

• Language: Python 3.x
• Libraries used: sys (for terminal arguments), math, and custom modules.
• Key Concepts: Object-Oriented Programming (OOP), Generators, Class Inheritance, and Data Parsing.

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Created with ❤️ for the Bioinformatics community.