Python for Bioinformatics (intermediate - some Python experience required)



Course Python for Bioinformatics
Instructor TBA, Physalia Courses
Date 05.06.2024 - 07.06.2024
Time 9:00 – 13:00
Duration ca. 12 hours
Type Online
ECTS 0.5


Course description:

Embark on a dynamic three-day journey into the world of bioinformatics with Python. This course is meticulously designed to establish the foundational knowledge and typical bioinformatics workflows essential for harnessing the power of the Python programming language. Throughout this immersive experience, participants will explore intermediate to advanced Python concepts while applying them to real-world scenarios commonly encountered in the field of bioinformatics.


Target Audience:

This course caters to biologists at all levels, including students, researchers, and group leaders, who possess a fundamental understanding of python programming.


Course Content:

  • Introduction to Data Science and Its Applications in Biology
  • Exploring Intermediate Python: Functions, Classes, Modules, Tips & Tricks
  • Data Preprocessing and Wrangling
  • In-Depth Exploration of Common Case Studies (e.g., Sequence Analysis and Alignment, Next-Generation Sequencing Data Processing, Genome Manipulation, Population Genetics, Data Retrieval from Public Databases)
  • Constructing Bioinformatics Pipelines
  • Introduction and Theoretical Foundations of Machine Learning
  • Delving into Supervised, Unsupervised, and Reinforcement Learning
  • Familiarity with Commonly Used Machine Learning Algorithms
  • Mastering Feature Engineering and Selection
  • Understanding Train-Test Split and Cross-Validation Techniques
  • Hands-On Experience with scikit-learn


Learning Outcomes:

By the conclusion of this course, participants will have acquired the following proficiencies:

  • Comprehend the distinct phases of a bioinformatics workflow.
  • Craft Python code for the preparation, processing, analysis, and visualization of biological data.
  • Create automated Python workflows tailored to bioinformatics pipelines.
  • Grasp the fundamentals of machine learning using Python.


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