https://github.com/elcharitas/bioinformatics_zero_to_hero
Bioinformatics with BioPython Course Guide
https://github.com/elcharitas/bioinformatics_zero_to_hero
biopython
Last synced: 6 months ago
JSON representation
Bioinformatics with BioPython Course Guide
- Host: GitHub
- URL: https://github.com/elcharitas/bioinformatics_zero_to_hero
- Owner: elcharitas
- Created: 2024-12-16T10:32:06.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2024-12-18T12:03:41.000Z (over 1 year ago)
- Last Synced: 2025-05-20T10:11:24.479Z (about 1 year ago)
- Topics: biopython
- Language: Python
- Homepage:
- Size: 26.4 KB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
**Zero to Hero BioPython for Bioinformatics**
### **Part 1: Learning Python Fundamentals**
**Module 1: Introduction to Python**
- Overview of Python and its applications in bioinformatics.
- Installation and setup (Python, IDEs, Jupyter Notebook).
- Writing your first Python script.
**Module 2: Python Syntax and Basics**
- Variables and data types.
- Basic operators (arithmetic, logical, and comparison).
- Input and output operations.
**Module 3: Control Structures**
- Conditional statements (if-else).
- Loops (for and while).
- Use cases in bioinformatics (e.g., DNA sequence analysis).
**Module 4: Functions and Modules**
- Writing and calling functions.
- Scope and arguments.
- Importing and using Python modules.
**Module 5: Data Structures**
- Lists, tuples, and dictionaries.
- Operations and methods on these structures.
- Applications in sequence data storage and manipulation.
**Module 6: File Handling**
- Reading and writing files.
- Working with FASTA and CSV files.
- Error handling in file operations.
**Module 7: Introduction to Libraries**
- Overview of useful Python libraries (NumPy, pandas, matplotlib).
- Installing libraries using pip.
**Module 8: Data Visualization**
- Plotting data using matplotlib.
- Simple bioinformatics visualizations (e.g., GC content graphs).
**Module 9: Regular Expressions**
- Pattern matching with the `re` module.
- Extracting motifs from DNA sequences.
**Module 10: Debugging and Optimization**
- Debugging techniques and tools.
- Optimizing Python code for performance.
---
### **Part 2: Learning BioPython**
**Module 1: Introduction to BioPython**
- Overview of BioPython and its ecosystem.
- Installing BioPython.
- Structure and key modules of BioPython.
**Module 2: Working with Sequence Data**
- Reading and writing sequence files (FASTA, GenBank).
- Manipulating sequences with `Seq` and `SeqRecord` objects.
**Module 3: Sequence Alignments**
- Pairwise sequence alignments.
- Global and local alignment techniques using Bio.Align.
**Module 4: Handling Biological Databases**
- Accessing NCBI databases using Bio.Entrez.
- Retrieving sequence data (e.g., protein or gene sequences).
**Module 5: Phylogenetics with BioPython**
- Parsing phylogenetic trees.
- Visualization and manipulation of trees using Bio.Phylo.
**Module 6: Working with Biological Features**
- Parsing annotation files (GFF, GenBank).
- Extracting features like genes and promoters.
**Module 7: Protein Analysis**
- Working with protein sequences.
- Calculating molecular weight and isoelectric point.
**Module 8: Parsing and Analyzing Structures**
- Working with PDB files.
- Analyzing 3D structures using Bio.PDB.
**Module 9: Simulating Sequence Evolution**
- Tools for simulating sequence evolution.
- Creating randomized sequences and testing mutations.
**Module 10: Advanced Topics and Custom Scripts**
- Writing custom scripts for complex workflows.
- Combining BioPython with other libraries for comprehensive analyses.
---
### **Part 3: Project Module**
**Module 1: Capstone Project**
- Choose a project based on personal or academic interest (examples):
- Building a tool to analyze and visualize GC content across multiple sequences.
- Automating phylogenetic tree generation from NCBI data.
- Parsing and analyzing protein structures.
- Presenting the final project with documentation and results.