The Praxis Bioinformatics with R Studio journey leverages AI-powered curation, hands-on data-intensive compute environments (Praxis Cloud), video assessment, quizzes, and expert mentoring to teach students how to use bioinformatics workflows to solve today’s toughest genomics problems. The online program is available 24x7x365 via any web browser or mobile device and includes three (3) Learning Paths, nine (9) Skills, and over twenty-five (25) hours of learning material.
Graduates of this course will earn a Bioinformatics with R digital credential – issued by Praxis AI. This BioHacker badge will showcase your experiential skills in data structures, R markdown, differential gene expression, gene characterization, and phylogenic analysis. The Bioinformatics with R credential was built in collaboration with world-renowned professor Josh Vandenbrink, currently at Louisiana Tech University.
Additional Details: https://vdb-lab.weebly.com/
Each Skill includes curated resources and assignments that involve the following:
- WATCH (Videos)
- READ (Guides/Articles)
- DISCUSS (Concepts with peers via a discussion board)
- DO (Virtual Labs with live access to R Studio)
- REVIEW (Quizzes to reinforce concepts and demonstrate mastery)
Learning Journey Overview
The Praxis Bioinformatics with R Learning Journey contains three (3) Learning Paths, nine (9) Skills, and over twenty-five (25) hours of learning material. Each Path is a collection of Skills:
- Introduction to Bioinformatics
- Introduction To Data Structures
- Models, Formulas and Basic Graphing
- Introduction to Reproducible Research
- R Markdown
- Differential Gene Expression
- Gene Characterization
- Phylogenic Analysis
- Remote Data Sources
Bioinformatics is a dynamic scientific discipline that utilizes computational and statistical methods for solving biological problems. A major theme in bioinformatics is to integrate and understand biological data generated by genome sequencing projects and other high-throughput molecular biology efforts. Bioinformatics tools are developed to reveal fundamental mechanisms underlying the structure and function of macromolecules, biochemical pathways, disease processes, and genome evolution.
Although many bioinformatics problems are solved by computation and programming, this course itself does not require (practical) computer programming. However, it is expected that all of the students learn how to use the available bioinformatics software to solve biological problems. The aim is to emphasize critical thinking: understanding how these tools work in principle and developing a computational mind for biological problems.