Bioinformatics aims at extraction of information from genetic data. Statistical methods used toward this end are the focus of statistical bioinformatics.
Technological developments in molecular biology over the last two decades have improved the knowledge of molecular and cellular processes underlying diseases and treatment effects. “Omics”-oriented approaches (such as genomics, transcriptomics, or proteomics) consider all molecules collectively instead of one molecule at a time, generating a system-wide understanding. Data obtained with the help of “omics” technologies are usually very voluminous (yielding even millions of measurements per single biological sample), highly structured, and complex.
Analysis of such data is not trivial and has become a specialty of its own. Of course, good knowledge of “classical” statistical methodology is required and training in this respect is offered in the first year of our program. Additionally, an introduction to medical and molecular biology is offered, together with an introductory training in programming. The second year focuses on the methods specific for the analysis of genomic and proteomic data obtained by using technologies like next-generation sequencing, mass spectrometry, etc. Methods for integrative analyses of different types of data are considered, too.
Bioinformatics is an interdisciplinary science. Statisticians working in this domain need to be able to communicate with researchers of various fields, report results, and give effective presentations. Developing such skills is an integral part of the program.
The “omics” revolution is a fact. Specialists capable of designing, analyzing, and interpreting of “omics” experiments can support fundamental research in academia, but also work in teams looking for, e.g., novel, molecular-biology-driven drug targets in biotech and pharma companies. Thus, such specialists are in high demand by universities, research institutions, biotechnology companies, and pharmaceutical industry. While the demand has been already present in the developed world, it also increases in the developing countries. It is thus a safe bet that the number of working places in statistical bioinformatics will only increase in the years to come.
With the constant evolution of high-throughput technologies, the future of biomedical research has been projected to be at the molecular level. These advanced genomic and proteomic technologies generate large amount of data that require multi-disciplinary expertise to handle and derive useful information from the generated data. This often requires a blend of biological, database management, computer programming, data mining, and advanced statistical skills.
Despite being an intensive program, the Master of Statistics and Data Science – Bioinformatics trajectory produces multi-disciplinary expertise in such a way that it provides its graduates with the necessary background and/or hands-on experience in molecular biology, database management, data mining algorithms, standard and advanced statistical modeling, reporting, communication, and, in summary, being an independent professional and a great team player.
Coming from a mathematical and computing background, this master trajectory equipped me with the relevant biological and statistical knowledge that, in turn, earned me the position of a statistical bioinformatics consultant (in charge of all high-dimensional experimental designs, data-preprocessing, data analyses, and analyses pipelines) at Erasmus University in Rotterdam and a PhD Fellow (with focus on class prediction with high-dimensional data) at Utrecht University.
(Victor Lih Jong, Cameroon)
Programme coordinator: prof. dr. Tomasz Burzykowski (tomasz.burzykowski[at]uhasselt.be)
Administrative info: Peter Vandoren (peter.vandoren[at]uhasselt.be)