This computational biology course will provide students hands-on experience using data-intensive computational and statistical methods to discover and interpret molecular systems underlying human phenotypes. Students will build on prior Linux command line experience to learn how to employ modern data transfer techniques, workflow managers, container technology, and software repositories to process large biological datasets. Data-intensive bioinformatics workflows will be applied by the student to process large human wild-type and cancer datasets. Representative workflows include high-throughput RNA profiling, differential gene expression analysis, co-expression network analysis, biomarker discovery using artificial intelligence and network biology approaches, functional enrichment analysis, and integrating individual patient samples for precision medicine applications.
The Praxis Medical Bioinformatics Learning Journey contains six (6) Learning Paths. Each Path is a collection of Skills:
- Research Computing Skills
- Biomedical Datasets
- Fundamental Genomic Workflows
- Biomarker Discovery
- Publishing Scientific Results
- Wrap-Up
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 you apply these workflows, you will be taught how to a Linux-based research computing system and understand the formats and locations of open-source biomedical datasets. We will learn some basic data visualization and publishing techniques. The computational skills you will learn are dovetail with molecular biology skills. The skills you will learn are highly sought after in the marketplace and will position you to be a modern biologist.