Students of Lewis University's concentration and certificate in computational biology and bioinformatics can certainly expect to learn about cutting-edge technologies, and they will have opportunities to use their skills in hands-on settings. However, upon entering the program, some students may have misconceptions about where computational biology ends and where bioinformatics begins.
These two fields, both of which are encompassed by Lewis’s online Master of Science in Data Science (MSDS) program, are often grouped together because they involve using computer science in understanding data collected by biologists and health sciences professionals. They share similarities in the problems they aim to solve and their open-sourced approach to development and sharing research. Both fields interact with a wide range disciplines within biology, including genetics and genomics, biochemistry, biophysics, cell biology and evolution. Whether something is in the realm of computational biology or bioinformatics, however, is more than just semantics.
The differences between the fields are subtle but practical. The National Institutes of Health defines the use of computational biology as “data-analytical and theoretical methods, mathematical modeling and computational simulation techniques to the study of biological, behavioral, and social systems.”1 Computational biologists tend to draw upon skills in development of algorithms, mathematical modeling, and statistical evaluation to make inferences from complicated data sets.
Bioinformatics, on the other hand, uses computational tools and approaches to expand the use of “biological, medical, behavioral or health data, including those to acquire, store, organize, archive, analyze, or visualize such data.” 1Bioinformatics approaches tend to draw upon skills in software development, database development and management, and visualization methods to convey information contained within data sets.
Simply put, computational biology is about studying biology using computational techniques, which further the understanding of the science. Bioinformatics focuses more on the engineering side and the creation of tools that work with biological data to solve problems.
These differences are best demonstrated with recent research in each field. Advances in the field of computational biology include a new genetic anomaly detection system that has already discovered a novel stress response affecting the fetuses of obese mothers in the second trimester2. Other advances include a technique to illuminate the ways that genes affect the function of 144 different types of human tissues3 and a breakthrough in understanding the way Dengue fever relies on the host's metabolism to reproduce4.
In bioinformatics, a recent study also took on Dengue fever by modeling the way infecting wild populations of mosquitoes with bacteria affects the spread of the virus5. Bioinformatics is particularly popular in the field of oncology, so anyone interested in cancer research would benefit from an understanding of the types of analysis and patient-specific treatments that could be achieved through bioinformatics.
Other recent research has sought to understand the development, or pathogenesis, of diseases such as macular degeneration6 and Lou Gehrig's disease7. The research is so versatile that it includes analyses of medical teleconsultation workspaces8, workflows for treating pediatric asthma patients9 and strength training intensity sensors10.
The future is bright for both these fields. Considering the constant increases in computing power and storage capabilities that make analysis of larger data sets possible and faster, even the human genome is no longer as intimidating to researchers with new ideas. Still, these advances require the talents of individuals with strong computational skills to address how data are effectively shared, stored and analyzed.11
Regardless of which field of study interests students of Lewis University's MSDS Computational Biology and Bioinformatics program, they can expect the intersection of biology and computer science will be filled with opportunities to make a lasting impact on the world.