2. Foundational concepts and skills for computational biology

Table of contents

• 2.1. Typing
• 2.2. Software engineering
  • 2.2.1. An introduction to Python
  • 2.2.2. Numerical computing with NumPy
  • 2.2.3. Plotting data with matplotlib
  • 2.2.4. Developing database, command line, and web-based programs with Python
  • 2.2.5. Writing code for Python 2 and 3
  • 2.2.6. Organizing Python code into functions, classes, and modules
  • 2.2.7. Structuring Python projects
  • 2.2.8. Revisioning code with Git, GitHub, and Meld
  • 2.2.9. Testing Python code with unittest, pytest, and Coverage
  • 2.2.10. Debugging Python code using the PyCharm debugger
  • 2.2.11. Documenting Python code with Sphinx
  • 2.2.12. Continuously testing Python code with CircleCI, Coveralls, Code Climate, and the Karr Lab’s dashboards
  • 2.2.13. Distributing Python software with GitHub, PyPI, Docker Hub, and Read The Docs
  • 2.2.14. Recommended Python development tools
  • 2.2.15. Comparison between Python and other languages
• 2.3. Linux
  • 2.3.1. How to build a Linux Mint virtual machine with Virtual Box
  • 2.3.2. How to build a Ubuntu Linux image with Docker
  • 2.3.3. An introduction to Linux Mint
• 2.4. Version and sharing data with Quilt
  • 2.4.1. Overview
  • 2.4.2. Using Quilt
• 2.5. Scientific communication: papers, presentations, graphics
  • 2.5.1. Writing manuscripts
  • 2.5.2. Reviewing manuscripts
  • 2.5.3. Making posters
  • 2.5.4. Making presentations
  • 2.5.5. Visualizing data
  • 2.5.6. Formatting textual documents with LaTeX
  • 2.5.7. Drawing vector graphics with Adobe Illustrator and Inkscape
  • 2.5.8. Editing raster graphics with Gimp