What is bioinformatics?
Bioinformatics is a field of study that combines two important disciplines - computer science and biological research. People who work in bioinformatics (e.g. bioinformatics analysts and engineers) apply computational tools to biological data in order to answer complex biological questions. This field has arisen due to the advent of biological experiments that produce extremely large quantities of data requiring interpretation and analysis. Such experiments include whole-genome sequencing, microarrays, genome-wide association studies, proteomics, transcriptomics, metabolomics, and more.
Perhaps the most visible area of biological data explosion is that of DNA sequencing. Continuing improvements in sequencing technology produce larger and larger data sets for less and less cost. Fifteen years ago, few microbiologists would have believed that they could obtain the complete genome sequence for their bacterium of interest within a few weeks and at a cost of only a few thousand dollars, but that has become a reality. Sequencing projects that in the past could have taken months to years to finish can now be completed within days or even hours. The result is that DNA sequencing is becoming just one more item in the laboratory toolkit and is being applied to more and more types of biological questions.
Virtually all fields of biology are embracing the use of bioinformatics tools in their work; from infectious disease research to environmental studies to personalized medicine, bioinformatics is playing a huge role. Since producing large datasets is increasingly quick and easy, the bottleneck has shifted from data production to downstream analysis. This is where the challenges arise for those in bioinformatics who are charged with creating tools that can aid in the interpretation of huge datasets.
For sequencing data, one challenge is annotation; turning the string of bases into meaningful predictions for the locations and functions of genes and other genomic features. The development of pipelines for genome annotation and analysis requires the combined efforts of biologists, who understand the data and questions that need to be answered, and computer scientists, who can create the software tools to accomplish the desired task.
Working in bioinformatics
Typically, people enter bioinformatics work primarily from two different backgrounds; either they have statistics or programming expertise and then developed familiarity with biological systems, or they have biological backgrounds and then learned programming skills. This creates a continuum with programming experts at one end and “pure” microbiology researchers at the other end. People working in bioinformatics can find themselves anywhere along this continuum, combining different amounts of biology and computer science depending on their interests and skill sets.
Today’s microbiology graduate students are typically exposed to some bioinformatics at least in their coursework and likely in their thesis work as well. They may use various software tools such as BLAST or other online resources. Those microbiology students who think they might be interested in pursuing a career in bioinformatics should seek out opportunities to learn more about it. They should consider taking bioinformatics electives and exploring programming languages such as Perl. This will allow them to find out whether they like programming and help them better decide where on the bioinformatics continuum they would most be comfortable. Here’s a short video about careers in bioinformatics.
At our research center, we have an ever-expanding bioinformatics department, with researchers and faculty who have multidisciplinary backgrounds. There are multiple opportunities for bioinformatics work at all locations on the biology/computer science continuum. At the heart of all of our work are the biological questions we are hoping to answer, thus all of our faculty and much of the bioinformatics staff have advanced degrees in biology.
What are some examples of bioinformatics research projects and what advice do we give to scientists who would like a career in bioinformatics?
I’ll continue this post in Part 2.