LII:Demystifying Biomedical Big Data: A User's Guide

Title: Demystifying Biomedical Big Data: A User's Guide

Author for citation: Haddad et al.

License for content: Unknown

Publication date: 2019

This is a Georgetown University course that is released on the edX platform. The eight-week course is designed to provide greater "understanding, analysis, and interpretation of biomedical big data to those in the biomedical field with limited or no significant experience in bioinformatics." The course is free to take, with a Verified Certificate of completion available for $49. The course requires on average three to six hours a week of effort.

The edX course description:

"The goal of this course is to 'demystify' the process of analyzing biomedical big data through a series of lectures and online hands-on training sessions and demos. You will learn how to use publicly available online resources and tools for genomic, transcriptomic, and proteomic data analysis, as well as other analytic tools and online resources. This course is funded by a research grant from the US National Institutes of Health (NIH)-Big Data to Knowledge (BD2K) Initiative.

What you'll learn:

Understand how biomedical data are being generated and processed
Learn about various biomedical big data resources (e.g. TCGA, G-DOC, UNIPROT, etc.)
Explore and analyze genomic, transcriptomic, and proteomic data using various online analysis tools
Make sense of big data using systems biology resources and tools
Appreciate the value of big data in biomedical research and clinical practice (e.g. enabling precision medicine)"

About the authors

Eleven instructors are affiliated with this course in some fashion. To learn more about each instructor, go to the edX course page and click on the name of each instructor.

General layout and contents of the course

The pre-enrollment syllabus outlines the course over the eight-week period. The first week provides an introduction to the course and to bioinformatics applications and the big data associated with them. Week two delves into translational research and big data, while week three gets into the big data aspects of DNA and it's sequencing. Week four takes a look at RNA through gene expression and MicroRNA, while week five addresses protein sequences, interactions, and analyses. Week six expands upon proteins by delving into proteomics, and week seven addresses systems biology. The final week offers a wide variety of perspectives of individuals in the field.