Why pursue bioinformatics? Not only is bioinformatics expected to be a growing field for jobs, with employment opportunities at many levels of commitment, but it also promises to be instrumental in increasing our understanding of biology and in the creation of new medical treatments for a host of deceases. It offers those of a technical bent many intriguing problems in biology, chemistry, mathematics, computer and information science. Others can apply the expertise to many unsolved biological and medical questions in creative and innovative ways.
In the last twenty years biologists have developed methods for generating awe-inspiring amounts of information. DNA
sequences from hundreds of organisms provide challenges for extracting biological and/or useful medical information. High throughput experimental procedures like microarrays can assay a cell’s total mRNA or protein content. And although this allows the laboratory biologist to dissect the processes of cell response, cell differentiation and decease processes in great detail, it raises difficult questions about reading real responses above statistical noise and in controls across different experiments. These problems offer fascinating new challenges for both computer scientists and statisticians to interpret this information. And last, ever increasing computation power opens the possibility of doing some biology in silico, that is, working solely on computer models of living organisms. Such models have already led to new insights in our understanding of the folding of RNAs and proteins, but physical chemists and computer modelers have just scratched the surface of this potential.
Many applications to medicine and biology
In the area of medicine, bioinformatics tackles problems of identifying disease genes both from the huge amount of DNA sequence now available, and from population studies. Using these techniques and more, bioinformatics has already opened new avenues for identifying useful drugs. Practically, the identification of disease genes has allowed, in some instances, the replacement of the affected proteins. And last, bioinformatic comparison of infectious viral and bacterial genomes have given indications of what makes a particular strain virulent.
Applied to biology, these techniques have led to a better understanding of how extent animals are related evolutionally. Comparison of homologous genes across organisms has and continues to clarify what are the important nucleotides in a gene. In silico protein folding has provided information about the chemistry of catalysis, giving insights into how genes control biological processes. Despite these successes many fascinating problems remain. Especially intriguing are problems of the control of genes and the mechanisms by which this control leads to development of organisms. Much of this will be done in the laboratory, but bioinformatics will be an integral part.
Challenges for mathematics, statistics and computer science
So, the explosion of biological information has opened several challenges for mathematics, statistics and computer science. In mathematics, the biologist has learned that the linear DNA code is not enough to understand an organism and that what is needed is an understanding of how genes are linked in networks. This has led to new challenges for mathematicians to understand such networks. New challenges for statistics come from the variability of high through-put experiments. Statisticians are working to develop techniques to control for this variation between experiments. Challenges for computer science include the development of algorithms for rapidly processing huge amounts of information and of in silico biology.
Why study bioinformatics here?
Students can tailor the bioinformatics major to their interests, focusing more on either experimental or computational approaches. The major is capped by a bioinformatics seminar in which students explore and discuss cutting-edge research in the field.
Undergraduates earning a bachelor of science degree in bioinformatics will have an interdisciplinary knowledge base ideally suited to pursuing graduate studies in bioinformatics, genomics, molecular biology, computational biology, protein chemistry and allied fields.