๐Ÿ

Master Python
for Biology

A practical programming course for Year 3 Life Sciences students at the University of Sussex. No prior coding experience required!

5
Core Sessions
3
Specialisation Tracks
100%
Biology Focused
1
Final Project

Core Sessions

Master the Python fundamentals through hands-on biological applications. All students complete these five essential sessions.

Available
1

Lab Calculations

  • โ–ธIntroduction to Python
  • โ–ธTypes and assignment
  • โ–ธFor loops
  • โ–ธLists and file I/O
Available
2

Analysing DNA

  • โ–ธString operations
  • โ–ธSequence file formats
  • โ–ธFile I/O
  • โ–ธBiopython
Available
3

Analysing DepMap Data

  • โ–ธObject-oriented programming
  • โ–ธPandas DataFrames
  • โ–ธCancer dependency analysis
Available
4

Explorative Data Analysis

  • โ–ธVectorisation
  • โ–ธExplorative data analysis techniques
  • โ–ธVisualization principles
  • โ–ธMatplotlib for scientific plots
Available
5

End to End Data Mining Project

  • โ–ธLinear regression analysis
  • โ–ธSeaborn for publication-ready plots
  • โ–ธStatistics and SciPy
  • โ–ธExploring new packages on PyPI

DNA Analysis Task

Put your Python skills to the test with a comprehensive DNA sequencing analysis project. Learn NGS fundamentals and perform real mutation analysis.

๐Ÿงฌ

Sequence Analysis Task

Apply your Python knowledge to real genomic data analysis

๐Ÿ“Š

Learn NGS Fundamentals

Understand sequencing technologies, FASTQ format, and quality control

๐Ÿ”

Sequence Analysis

Work with real sequencing data, compare reads to reference and call variants

๐Ÿงช

Mutation Counting

Build your own mutation analysis pipeline and discover variants

๐ŸŽฏ Project Overview

What You'll Build
  • โ€ข FASTQ quality assessment tool
  • โ€ข Read comparison to reference sequence
  • โ€ข Mutation detection algorithm
  • โ€ข Publication-ready scientific figures
Skills You'll Gain
  • โ€ข Reading bioinformatics file formats (FASTA)
  • โ€ข Large dataset processing
  • โ€ข Descriptive statistics of variants
  • โ€ข Research-grade Python coding
๐Ÿ“‹View Assignment Details

Available after Lecture 3 - Complete the core sessions first to build the foundation skills

Final Project

Apply everything you've learned to explore large-scale genomic datasets. Become a bioinformatician through hands-on data analysis.

Capstone Project
๐Ÿงฌ

Become a Bioinformatician

Explore large gene effect and expression data with EDA and correlation analysis:

  • โ˜…Explore large gene effect datasets from DepMap
  • โ˜…Analyze gene expression patterns across cancer cell lines
  • โ˜…Perform correlation analysis to identify genetic dependencies
  • โ˜…Create publication-ready visualizations of genomic data

Specialisation Tracks

Choose one track to deepen your skills for your final project. Ambitious students are encouraged to explore all three tracks.

Coming Soon
6

Image Analysis Track

  • โ–ธNumPy and scikit-image basics
  • โ–ธMicroscopy image processing
  • โ–ธCell segmentation and tracking
  • โ–ธBatch analysis pipelines
Coming Soon
7

Data Analysis & Visualization Track

  • โ–ธPandas for biological data
  • โ–ธStatistical analysis with SciPy
  • โ–ธCreating publication-ready figures
  • โ–ธAnalyzing experimental results
Coming Soon
8

Text Analysis & AI Track

  • โ–ธWorking with LLMs for biology
  • โ–ธAutomating literature searches
  • โ–ธText mining PubMed abstracts
  • โ–ธBuilding research assistants

Practical Seminars

10 hands-on sessions: 5 lecture support labs + 5 capstone project sessions

๐Ÿ“š Phase 1: Lecture Support (Sessions 1-5)

Practice sessions that reinforce each lecture with guided notebook exercises. Work through problems step-by-step with instructor support.

๐Ÿ“

Session 1

Python Fundamentals Lab

Variables, calculations, and basic programming concepts

Open Notebook
๐Ÿ“

Session 2

DNA Analysis Workshop

String manipulation and sequence analysis techniques

Open Notebook
๐Ÿ“

Session 3

OOP and Pandas Data Workshop

First steps working with Python packages and Pandas DataFrames

Open Notebook
๐Ÿ“

Session 4

Matplotlib and Vidualisation Workshop

Generating publication-ready plots and visualisations

Open Notebook
๐Ÿ“

Session 5

End to End Analysis Workshop

Gene Dependency Correlation Analysis with Statistics and Visualisation

Open Notebook

๐Ÿš€ Phase 2: Project Launch (Session 6)

๐ŸŽฏ

Capstone Project Introduction

Introduction to your final capstone project: building a comprehensive gene analysis pipeline. Learn about project requirements, choose your biological dataset, and plan your approach.

Session 6 Topics:
  • โ€ข Project overview and requirements
  • โ€ข Dataset selection guidance
  • โ€ข Pipeline architecture planning
  • โ€ข Collaboration and Git workflows
Deliverables:
  • โ€ข Project proposal draft
  • โ€ข Dataset identification
  • โ€ข Development environment setup
  • โ€ข Timeline and milestone planning

๐Ÿ› ๏ธ Phase 3: Project Development (Sessions 7-10)

โšก

Guided Project Work Sessions

Four dedicated sessions to build your capstone project with instructor guidance. Get help debugging code, implementing features, and preparing your final presentation.

Session Focus Areas:
Session 7:Data preprocessing and quality control
Session 8:Analysis pipeline implementation
Session 9:Visualization and interpretation
Session 10:Final debugging and presentation prep
Support Available:
  • โ€ข One-on-one debugging sessions
  • โ€ข Code review and optimization
  • โ€ข Statistical analysis guidance
  • โ€ข Presentation skills workshop
  • โ€ข Peer collaboration time
  • โ€ข Final project submission prep

Learning Resources

Course Schedule

WeekLecture TopicSeminarAssignment
1Introduction to Python & SetupLab calculator workshop
2Strings & DNA AnalysisSequence Analysis Workshop
3Object Oriented Programming and intro to PandasDepmap Data Workshop
DNA Sequence Analysis, due Week7
4Linear Regression and Data VisualisationMatplotlin Seaborn Workshop
5End to End Data Mining projectGene Dependency Correlation Analysis Workshop
Final Project, due Week 11
Basic Python Skill Test

About the Course

This course is specifically designed for Year 3 students in the Life Sciences from the University of Sussex who want to add computational skills to their toolkit. But this course is also for anyone who wants to learn Python for biology!

What You'll Learn

  • โœ“Python programming fundamentals
  • โœ“Biological sequence analysis
  • โœ“Data processing and visualization
  • โœ“Automation of lab calculations

Prerequisites

  • โœ“No programming experience needed
  • โœ“Basic biology knowledge
  • โœ“A Google account (for Colab)
  • โœ“Enthusiasm to learn!