Abstract
BIOKDD'04 was held in conjunction with the 10th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, in Seattle, WA, in August 2004. There are numerous sources of biological data that provides challenging opportunities for data mining. For example, the structural genomics initiative aims to catalog the structure-function information for proteins. Advances in technology such as microarrays have launched the subfield of genomics and proteomics to study the genes, proteins, and the regulatory gene expression circuitry inside the cell. Other sources of data include the rapidly growing literature in bioinformatics (e.g., PubMed), the data on biochemical pathways, the evolutionary relationships among organisms in the Tree of Life, high throughput drug design combinatorial libraries, and so on. In addition to the data from biology and genomics, there are rich sources of data from other biosciences, including biomedical, and neuroscience data.
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