Bioinformatics illustrate a unique interdisciplinary approach to computing in modern biology. They combine Computer Science, Information Engineering, Mathematics, and Statistics to analyze and interpret biological data. Computer programming methodologies, such as Python, are applied in Bioinformatics for the purpose of managing the structure, function, evolution, mapping, and editing of genomes—or, an organism’s complete set of DNA.

Bioinformatics are critical to understanding normal versus abnormal genomes, and are even said to have sparked a revolution in medical discoveries. That is likely because Bioinformatics enables learners to leverage data and information from genomic datasets, helping to identify the genetic basis for diseases and providing a clearer path to finding treatments.

As big data proliferates in all fields, many new job opportunities lie in Data Science and Bioinformatics. Career opportunities start at Bioinformatician and branch out into careers in Bioengineering, Computational Science, Software Engineering, Machine Learning, Mathematics, Statistics, Molecular Biology, Biochemistry, Information Technology, Clinical Research, and other fields that heavily rely on information derived from genomes.

Learners interested in Bioinformatics will find hands-on courses that put them at the center of genome-related challenges.

Covering the basics, you’ll investigate DNA replication, the role of DNA patterns, and other ways to garner information from DNA. Methodologies you can explore include multiple sequence alignments, phylogenetics, gene expression data analysis, protein interaction networks, and more.

Learners can also experience real-life Bioinformatics scenarios within scientific settings. You'll discover algorithms for solving various biological problems, and take on assignments designed to help you implement these algorithms in Python.

Successful learners will be able to address many questions in modern biology that need a computational approach in order to be answered.