Journal of Data Mining en génomique et protéomique

Abstrait

Data Mining Empowers the Generation of a Novel Class of Chromosomespecific DNA Probes

H. Zeng, H.U.G. Weier, J. Kwan, M. Wang and B. O’Brien

Probes that allow accurate delineation of chromosome-specific DNA sequences in interphase or metaphase cell nuclei have become important clinical tools that deliver life-saving information about the gender or chromosomal make-up of a product of conception or the probability of an embryo to implant, as well as the definition of tumorspecific genetic signatures. Often such highly specific DNA probes are proprietary in nature and have been the result of extensive probe selection and optimization procedures. We describe a novel approach that eliminates costly and time consuming probe selection and testing by applying data mining and common bioinformatics tools. Similar to a rational drug design process in which drug-protein interactions are modeled in the computer, the rational probe design described here uses a set of criteria and publicly available bioinformatics software to select the desired probe molecules from libraries comprised of hundreds of thousands of probe molecules. Examples describe the selection of DNA probes for the human X and Y chromosomes, both with unprecedented performance, but in a similar fashion, this approach can be applied to other chromosomes or species.