Master Python
for Biology

A practical programming course for biology students. No prior coding experience required!

Start Learning →Watch Intro Video
8
Sessions
8
Labs
100%
Biology Focused
3
Assignments

Section 1: Python Basics

Build your Python foundations through hands-on biological applications. Sessions 1–4 take you from your first variable to writing robust, testable functions.

Available
1

Data Types, Variables and Basic Operations

  • ▸Variables and assignment
  • ▸Core types: int, float, bool, str
  • ▸Arithmetic and string operators
  • ▸print() and f-strings
SlidesLabsVideo
Available
2

From One Sequence to Many: Lists, Strings & Maps

  • ▸Lists: holding a collection of sequences
  • ▸Strings as sequences: indexing & slicing
  • ▸String methods: .replace(), .find()
  • ▸Dictionaries: mapping codons to amino acids
SlidesLabsVideo
Under Construction
3

Loops, Dictionaries and Control Flow

  • ▸for / while loops and range()
  • ▸if / elif / else
  • ▸Dictionaries and .items() iteration
  • ▸Building a codon translation table
SlidesLabsNotebooksVideo
Under Construction
4

Functions, Files and Error Handling

  • ▸Defining functions and return values
  • ▸Scope, type hints and docstrings
  • ▸Reading and writing files
  • ▸try / except and raising errors
SlidesLabsNotebooksVideo

Section 2: Python and Data in Biology

Four sessions, four real datasets, four real questions — one each from neurobiology, ecology, cancer biology and cell biology. Three of them come from labs in this building.

Under Construction
5

Arrays — One Neuron, Many Trials

🐭NeurobiologyWhisker touch — Maravall Lab, Sussex
  • ▸Packages, objects and methods
  • ▸numpy arrays and vectorisation
  • ▸Masking and finding events in a signal
  • ▸2-D arrays: averaging 254 trials into an answer
SlidesLabsNotebooksVideo
Under Construction
6

DataFrames — Who Pollinates Your Dinner?

🐝EcologyUrban pollinator survey — Nicholls Lab, Sussex
  • ▸A column is an array with a name
  • ▸Selecting columns, filtering rows
  • ▸value_counts and the effort trap
  • ▸groupby — split, add up, combine
SlidesLabsNotebooksVideo
Under Construction
7

Plotting and Exploratory Data Analysis

🧬Cancer biologyCancer Dependency Map (DepMap)
  • ▸matplotlib and seaborn
  • ▸Distributions, box plots and small multiples
  • ▸Scatter plots, correlation and statistics
  • ▸Building a publication-ready figure
SlidesLabsNotebooksVideo
Under Construction
8

Analysing Images in Python

🔬Cell biologyFluorescence microscopy — Hochegger Lab, Sussex
  • ▸An image is a 2-D array
  • ▸Cropping, indexing and displaying
  • ▸Otsu thresholding: finding the nuclei
  • ▸Counting, measuring, and a cell-cycle profile
SlidesLabsNotebooksVideo

Learning Resources

📓

Notebooks

Every practice notebook, by lab

🧬

Sample Data

Real sequences & datasets

📖

Cheat Sheets

Quick reference PDFs

🛠️

Dev Tools

Python IDEs & setup guides