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E-Learning, Training materials
Biology meets Programming - Introduction to Bioinformatics using Python
In the era following the completion of the Human Genome Project, biologists are confronted with the challenge of analyzing, interpreting, and visualizing vast and intricate datasets. A growing number of scientists have embraced the practice of creating small programs using scripting languages like Perl or Python. This course has been developed to educate students and researchers who lack prior programming experience but aspire, or require, to develop their own bioinformatics software tools.
If you possess an interest in analyzing extensive biological data or are intrigued by typical bioinformatics tasks such as sequence conversion and alignment, file parsing, and data visualization, this course offers you the opportunity to acquire fundamental skills in Python. By participating in this course, you will gain hands-on experience and develop a solid foundation in Python programming, enabling you to handle the challenges associated with bioinformatic activities effectively.
DOI: http://dx.doi.org/10.5447/ipk/2022/17
Contact: https://github.com/snowformatics/Bioinformatics/
Keywords: Python, Python biologists, Programming, Bioinformatics, Data Analysis, Sequence Analysis
Target audience: Beginner, PhD Students, Scientists
Resource type: E-Learning, Training materials
Status: Active
Prerequisites:
The training course caters to a diverse audience, including young scientists such as PhD students and postdocs, as well as experienced scientists who are keen to acquire Python programming skills.
Learning objectives:
The objective of this training course is to provide participants with an introductory understanding of the Python programming language through the resolution of common Bioinformatics tasks.
List of Topics:
- Manipulating strings, lists, dictionaries, and slicing data.
- Working with conditions, if-statements, and for-loops.
- Reading, parsing, and converting bioinformatics file formats.
- Implementing bioinformatics algorithms.
Tools:
- Python 3
- Colaboratory (https://colab.research.google.com/) , Jupiter Notebooks (https://jupyter.org/) or Anaconda (https://www.anaconda.com/)
Please follow the course plan (https://github.com/snowformatics/Bioinformatics/blob/master/python_course062022/course_plan.pdf) , the material is also hosted on
GitHub.
Date created: 2022-07-06
Date published: 2022-07-28
Scientific topics: Bioinformatics, Biology
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