Using Python in Bioinformatics and the Laboratory
The Real Python Podcast
Modeling Anaerobic Digestion for Waste Management and Energy Production
Exploring how the AD Toolbox project utilizes microbial population manipulation and advanced modeling techniques to optimize anaerobic digestion processes for converting organic waste into valuable products like methane.
How is Python being used to automate processes in the laboratory? How can it speed up scientific work with DNA sequencing? This week on the show, Chemical Engineering PhD Student Parsa Ghadermazi is here to discuss Python in bioinformatics.
Parsa provides background on his research and the bioinformatic techniques used to discover gut microbes’ role in human health and diseases. We talk about automating lab experiments with liquid handling robots and Python.
We dig into libraries to shatter and reassemble DNA sequences. Parsa also shares current projects from the Chan Lab at Colorado State University and his GitHub repository.
Course Spotlight: Building Python Project Documentation With MkDocs
In this video course, you’ll learn how to build professional documentation for a Python package using MkDocs and mkdocstrings. These tools allow you to generate nice-looking and modern documentation from Markdown files and, more importantly, from your code’s docstrings.
Topics:
- 00:00:00 – Introduction
- 00:01:51 – Engineering Background and Current PhD Program
- 00:05:52 – What is Bioinformatics?
- 00:08:11 – Where do you use Python in the lab?
- 00:10:35 – Using lab robotics
- 00:15:22 – Python development environment
- 00:16:33 – Lab robotics allow for precision
- 00:19:03 – How are using these tools for research?
- 00:22:14 – What are the techniques for measurements?
- 00:26:17 – Video Course Spotlight
- 00:27:33 – How is the data output from the machine?
- 00:29:20 – Moving into DNA sequencing and extraction
- 00:32:08 – Shattering to work with smaller DNA sequences
- 00:34:34 – Python libraries for DNA re-assembly
- 00:36:28 – Building ADToolbox
- 00:40:24 – How do you store the data?
- 00:41:32 – Inferring microbial interactions
- 00:44:02 – Types of hardware used for these projects
- 00:47:07 – What are you excited about in the world of Python?
- 00:48:09 – What do you want to learn next?
- 00:49:16 – How can people follow your work online?
- 00:50:00 – Thanks and goodbye
Show Links:
- ParsaGhadermazi - GitHub
- Bioinformatics - Wikipedia
- Opentrons - Lab Automation - Lab Robots for Life Scientists
- Tutorial — Opentrons Python API V2 Documentation
- Serial Dilutions and Plating: Microbial Enumeration - Microbiology - JoVE
- What is Chromatogram & How to Read a Chromatogram?
- Episode #186: Exploring Python in Excel
- megahit: Ultra-fast and memory-efficient (meta-)genome assembler
- DRAM: Distilled and Refined Annotation of Metabolism - GitHub
- humann: HUMAnN 3.0 - HMP Unified Metabolic Analysis Network
- MetaPhlAn4 – The Huttenhower Lab
- ADToolbox - Tools for modeling and optimizing the anaerobic digestion process
- SPAM-DFBA - Algoritm for inferring microbial interactions
- Microbial interactions from a new perspective - Bioinformatics - Oxford Academic
- Alpine — Research Computing University of Colorado Boulder documentation
- MkDocs
- Build Your Python Project Documentation With MkDocs
- scikit-bio
- Episode #190: Great Starting Points for Contributing to Open Source
- Chan Lab at Colorado State University - GitHub
- ParsaGhadermazi - GitHub
- Parsa Ghadermazi - LinkedIn
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