Bioinformatics: Is Biology Finally Applied Mathematics?
Abstract
"In science there is only physics, all the rest is stamp collecting."
Ernest Rutherford
"There is no doubt that mathematics, physics, and other sciences rather ill-advisedly referred to as 'exact'...will continue to afford surprising discoveries-yet, I cannot help feeling that the real scientific revolution of the future must come from biology."
Ernst Mayr
The exact sciences have always been based on strong mathematical results. Physics and, with apologies to Lord Rutherford, chemistry takes the lead as exact sciences. Biology, while not exactly a soft science (at least to this biologist) has not achieved the same level of mathematical sophistication as physics and chemistry. Biostatistics has arisen to analyze data. Partial differential equations have been used to model population dynamics. Game theory is applied by evolutionists to model how a behavior or trait becomes prevalent or removed from a population. Unfortunately, none of these have risen to the level of a 'fundamental law', and the inherent variability present in biological systems makes these approaches approximate at best, though interesting and important areas of work.
Bioinformatics, a new area of biomathematics, has recently gained in importance and has done so on a grand scale--perhaps eventually to the level that Lord Rutherford would declare biology as an exact science. In this talk, I will discuss three hot areas of bioinformatics: sequence alignment, genomics, and proteomics. Each of these areas have become important because of the Human Genome Project which has determined (essentially) the entire sequence of human DNA--a string of 3,000,000,000 letters A, C, T, G representing the nucleotides in our chromosomes. Bioinformaticists are using and developing novel tools in applied mathematics, statistics, and computing to handle this data and extract information from it relevant to biology and medicine.
In this talk, I hope students will see that modern biology problems represent great opportunities for applied mathematicians.
About the Speaker: Dr. Shannon received his Ph.D. in biostatistics from the University of Pittsburgh in 1995. Since then, he has been at Washington University School of Medicine and is currently Director of the Biostatistics Consulting Center in the Department of Medicine. His research interests include classification and clustering of biomedical data, large database analysis, computational statistics, data mining, and decision theory.