Learn how to analyze biological big data to unlock the next big biotech discovery.
- 8weeks long
- 8-10 hours per week
- Learn for FREE, Ugpradable
- Self-Paced
- Taught by: James Coker, Associate Professor and Program Chair, Bioinformatics and Biotechnology Regulatory Affairs Specializations
- View Course Syllabus
Online Course Details:
Modern biology generates massive quantities of big data. Hidden in this data might be the next blockbuster cancer therapy, the definitive proof that a certain gene is responsible for a disease, or the information needed to replicate a crucial biological process — and you could be on the team that discovers it.
Bioinformatics blends biology, computer science and mathematics and in this Bioinformatics MicroMasters program you’ll gain the cutting edge knowledge and experience that will give you significant career advantage in this fascinating field.
In this program, you will learn how to analyze DNA sequences to find mutations and anomalies, understand the important role protein structure plays in protein function and use statistical analysis tools, including R programming, to mine biological big data.
This program is ideal for those who want to learn more about the bioinformatics field and its effects on society at large or who would like to incorporate bioinformatics principles and tools into their laboratories.
Job Outlook:
- Bioinformatics Scientist is expected to grow rapidly in the next several years and have roughly 10,000 new job openings from 2014-2024 (O*Net Online).
- Medical Scientist is expected to grow at 8% from 2014-2024 resulting in 9,000 new jobs (BLS).
- Top industries are the government, private, scientific, and technical services sectors for careers in positions such as bioinformatician, bioinformatics analyst, bioinformatics software engineer, and bioinformatics scientist (O*net online).
Explore the fundamentals of bioinformatics by checking out our guide on biology meets programming.“
What You’ll Learn:
- How to align DNA/RNA and protein sequences and the theory behind the algorithms that make them possible
- The effects of mutations on cellular processes and the structure of proteins
- How to generate model structure of proteins
- Basic R programming to analyze biological data
- How to apply packages in the R environment to typical problems in bioinformatics
