https://github.com/mjmolina/europython_2019
Europython 2019 Talk - When a Biologist met Python.
https://github.com/mjmolina/europython_2019
biopython bokeh networkx pytorch rdkit
Last synced: 5 months ago
JSON representation
Europython 2019 Talk - When a Biologist met Python.
- Host: GitHub
- URL: https://github.com/mjmolina/europython_2019
- Owner: mjmolina
- Created: 2019-07-07T18:55:49.000Z (over 6 years ago)
- Default Branch: master
- Last Pushed: 2020-12-02T23:11:37.000Z (about 5 years ago)
- Last Synced: 2025-02-24T08:41:38.591Z (12 months ago)
- Topics: biopython, bokeh, networkx, pytorch, rdkit
- Language: Jupyter Notebook
- Homepage:
- Size: 1.29 MB
- Stars: 1
- Watchers: 2
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# EuroPython 2019 :snake: :switzerland:
## When a Biologist met Python
### Talk description
Biology and computing are closer than we usually think, for example many algorithms are inspired in biology patterns, and complementary to that, researchers needs special algorithms to have a better understanding of our environment. Thus, there is a strong relation an dependency.
In the past years, Biology has been transformed into computational biology. Therefore
technological advances helps us to predict physical interactions between atoms and DNA, because we are being able to integrate information from biology into algorithms.
Python has become a popular programming language in biosciences because it has a clean syntax that makes it easy to read language. In addition to this, there are many modules (toolkits) extending to different biological domains, like metabolomics, structure analysis, phylogenomics, molecular biology and others. Python is currently improving researcher’s workflow, helping us to focus on the theory or experimental part, instead of fighting with old buggy applications.
This talk aims to be oriented to all audiences (with/without biological background) since we will go together through an amazing adventure into the natural sciences using tools like Biopython, Bokeh, Networkx, Ecopy and much more! Are you brave enough to follow me on this journey?
Type: Talk (30 mins); Python level: Beginner; Domain level: Beginner
Here you can find all the examples of the talk
* `example_avocado`, Bokeh interactive data visualization.
* `example_classifier`, PyTorch simple image classifier.
* `example_happiness`, Smile visualization with RDKit.
* `example_sas`, Script to query the PMC database with Biopython.
* `example_snakes` Detect a sequence of colors with Scikit-Image.
* `example_zika` NetworkX based animation to visualize the spread of viruses.