At expected data rates, the sequences generated each day for the next five years will represent hundreds of new genes and proteins. Zorn's Bioinformatics Group was already developing computational tools for this work in support of the Human Genome Grand Challenge. That work includes development of specialized software modules, database design and developing methods for indexing genomic information. But for it to be truly useful, we have to have it in an accessible format. The Genome Channel allows users to zoom in on a particular chromosome, then see how much of that chromosome has been sequenced.
Users can then bore down into each individual sequence and the accompanying annotation.
Implicit in the DNA sequence is a protein's three-dimensional topography, which in turn determines function. If there is a gene there, analyzing the folded structure of the accompanying protein can give scientists a clue as to the gene's characteristics. Inna Dubchak, a computer scientist at CBCG, has developed statistical-based models to predict fold classes of proteins. Such predictions are useful in that they can reduce the number of possible protein structures, thereby helping scientists zero in faster on those of most relevance. She then took the physical and chemical properties of the amino acids which make up proteins and represented each amino acid by a vector of its properties.