Technologies such as 2D gels and mass spectrometry offer glimpses into the world of mature proteins and their molecular interactions. Finally, we are stepping beyond analyzing generic genomes and are asking what genetic differences between individuals of a species are the key for predisposition to certain diseases and effectivity of special drugs. These questions join the fields of molecular biology, genetics, and pharmacy in what is commonly named pharmacogenomics. Pharmaceutical industry was the first branch of the economy to strongly engage in the new technology combining high-throughput experimentation with bioinformatics analysis. Medicine is following closely.
Medical applications step beyond trying to find new drugs on the basis of genomic data.
The aim here is to develop more effective diagnostic techniques and to optimize therapies. The first steps to engage computational biology in this quest have already been taken. While driven by the biological and medical demand, computational biology will also exert a strong impact onto information technology. Since, due to their complexity, we are not able to simulate biological processes on the basis of first principles, we resort to statistical learning and data mining techniques, methods that are at the heart of modern information technology. The mysterious encoding that Nature has afforded for biological signals as well as the enormous data volume present large challenges and are continuing to have large impact on the processes of information technology themselves.