🧬 Lecture 1: Python Fundamentals

Interactive Google Colab notebooks to learn Python programming for biology. Work through these in order for the best learning experience.

🎯 Getting Started

New to Python? Start with the "Welcome to Google Colab" notebook below.

Each notebook is interactive - you can run code, make changes, and see results immediately.

No installation needed - everything runs in your web browser using Google Colab.

Start Here

🚀 Welcome to Google Colab

Your introduction to Jupyter notebooks and the Colab environment

  • ▸What are notebooks and why use them?
  • ▸Understanding cells (code vs text)
  • ▸Running your first Python code
  • ▸Common mistakes and solutions
  • ▸Practice exercises
Open in Colab
Step 2

📦 Variables & Comments

Learn to store and organize your data with meaningful names

  • ▸What are variables and why use them?
  • ▸Python naming rules and conventions
  • ▸Writing helpful comments
  • ▸Variable assignment and updates
  • ▸Biology examples and practice
Open in Colab
Step 3

🔢 Data Types

Understanding different kinds of data: numbers, text, and more

  • ▸Integers for counting (cells, samples)
  • ▸Floats for measurements (pH, concentrations)
  • ▸Strings for text (gene names, sequences)
  • ▸Booleans for true/false states
  • ▸Type conversion and common errors
Open in Colab
Step 4

🎨 F-Strings & Formatting

Create beautiful, professional output for your biological data

  • ▸Modern string formatting with f-strings
  • ▸Controlling decimal places and precision
  • ▸Scientific notation and percentages
  • ▸Creating neat data tables
  • ▸Lab report formatting
Open in Colab
Step 5

🔧 Functions: Reusable Code

Package your calculations into reusable building blocks

  • ▸Why functions matter in programming
  • ▸Creating your first function
  • ▸Parameters and return values
  • ▸Functions with and without returns
  • ▸Default parameters and documentation
Open in Colab
Step 6

📋 Lists: Organizing Data

Store and organize multiple pieces of biological data

  • ▸Creating and accessing lists
  • ▸List indexing (starting from 0!)
  • ▸Lists of lists for complex data
  • ▸Adding and modifying list items
  • ▸Real biological examples
Open in Colab
Step 7

🔄 For Loops: Automation

Automatically process multiple samples and datasets

  • ▸Basic for loop syntax and concept
  • ▸Processing lists with calculations
  • ▸Combining functions and loops
  • ▸Quality control automation
  • ▸High-throughput data analysis
Open in Colab
Apply It!

🧪 Lab Calculator Toolkit

Real Python tools you'll actually use in the lab!

  • ▸DNA/RNA dilution calculator
  • ▸Molarity and molecular weight calculator
  • ▸PCR master mix calculator
  • ▸Protein yield calculator
  • ▸Growth rate calculator
Open in Colab

💡 Learning Tips

Work through in order: Each notebook builds on the previous ones.

Take your time: Run every code cell and try the exercises.

Experiment: Change values and see what happens - you can't break anything!

Save your work: Use "File → Save a copy in Drive" to keep your progress.

🚀 Quick Access

Lab Calculator Toolkit

📚 Part of the Python for Biologists course by Helfrid Hochegger

University of Sussex | Year 3 Biology, Biochemistry & Neuroscience