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Course Catalog > Medical Bioinformatics

Medical Bioinformatics

The Praxis Medical Bioinformatics journey – featuring famous cancer researcher Dr. Alex Feltus – leverages AI-powered curation, hands-on data-intensive computer environments, multisensory online resources, quizzes, and expert mentoring (featuring Discord) to teach students how to use bioinformatics workflows to solve today’s toughest genomics problems with a focus on gene expression changes between normal and cancer tissue.

Students will explore how computational environments such as Linux, Jupyter Notebooks, and Python impact biosciences and genomics. In addition, they will gain insights into genome data mining, cancer and normal transcriptomics, differential gene expression analysis, gone co-expression analysis, and biomarker discovery using data-intensive hands-on labs and AI-powered collaboration. Qualifies for the BioHacker: Cancer Transcriptomics digital badge.

Medical Bioinformatics

Journey Architecture

Medical Bioinformatics Detail Journey

The online program is available 24x7x365 via any web browser or mobile device and includes five (5) learning paths, twenty-one (21) lessons, and over seventy-five (75) hours of learning material. Below is a list of the main topics:

  • Research Computing Skills
  • Biomedical Datasets
  • Fundamental Genomics Workflows
  • Biomarker Discovery
  • Publishing Scientific Results

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.

Medical Bioinformatics is performing bioinformatics to understand the human organism.  It can be basic research, clinical research, or translational research.  In this course, we will focus on the basic and applied genomics workflows to understand normal and aberrant human phenotypes. Before students apply these workflows, they will be taught how to use a Linux-based research computing system and understand the formats and locations of open-source biomedical datasets. Students will learn some basic data visualization and publishing techniques. The computational skills taught are dovetail with molecular biology skills.  The skills transferred in this course are highly sought after in the marketplace and will position students to become modern biologists.

Skills and Resources

Medical Bioinformatics Detail Resources
  • Medical Bioinformatics
  • Using Jupyter Notebooks
  • NCBI Short Read Archive
  • Genomics Data Formats
  • Genome Data Commons (Cancer Datasets)
  • GEM Preprocessing
  • GCN Analysis  
  • Merging GTEX-TCGA Data
  • Gene List Analysis
  • Publishing code on GitHub
  • Introduction To Linux & Bash Scripting
  • How to use Advanced Computer Systems
  • Genotype-Phenotype Expression (GTEx)
  • GEM Construction
  • DEG Analysis
  • GRN Linking
  • Gene Oracle
  • How to write a scientific report
  • Publishing scientific reports

Digital Credential

Earners of the Cancer transcriptomics BioHacker credential have successfully demonstrated experiential skills in computational biology, genome data mining, structural bioinformatics, and systems biology. The Cancer transcriptomics badge requires 75+ hours of hands-on activities and labs across 20+ skills in biotech R&D. The Cancer transcriptomics BioHacker credential was built in collaboration with world renowned professor Alex Feltus, currently at Clemson University.

Following is summary of the earning criteria for the BioHackers: Cancer transcriptomics digital credential:

  • Complete 20+ hands-on cancer transcriptomics labs using live biological computing systems
  • AND – Complete all required learning resources in the Cancer transcriptomics online journey – 20+ lessons – including, videos, articles, activities, and discussion posts
  • AND – Pass short assessments (80% or better) in all lessons
  • AND – Participate in weekly virtual collaboration sessions with instructor(s), mentor(s), and peers
Cancer Transcriptomics