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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.‎

A background in biology, math, or programming can be useful in the study of bioinformatics. Coursework in biology, specifically molecular biology, can help you understand some of the terms you will encounter as you learn bioinformatics. You'll likely find some knowledge of basic calculus and linear algebra as well as descriptive and inferential statistics beneficial for learning and practicing bioinformatics analysis methods. Additionally, experience with database management or using a programming language like Python, R, or Java may also be useful as you explore bioinformatics methods and tools researchers use in their work.‎

People working in the field of bioinformatics come from diverse backgrounds, but what they have in common is a passion for analyzing data and a desire to understand the role of DNA in medicine. Some start their careers as computer scientists who decide to apply their skills to the study of molecular biology. Others are biologists who want to take a more active role in the analysis of laboratory discoveries. Many of them enter the field because it combines their interest in data science, programming, and biology. They typically thrive in environments where they learn new information and have a chance to apply their discoveries to real-world issues.‎

If you're fascinated by the natural world and enjoy discovering what makes people tick on a molecular level, then learning bioinformatics may be right for you. You'll be able to take a closer look at topics like DNA and RNA sequencing, protein interaction networks, and epigenetic patterns. Learning bioinformatics can help prepare you for a career shift if you already have a background in computer science or programming and want to apply it to research used to treat diseases like cancer. Bioinformatics is a broad field, so you have an opportunity to develop and enhance your skills that can be used in a variety of settings and roles, from laboratories to data warehouses.‎