Gene expression profiling is the characterization of cells based on the level of gene activity represented by concentrations of complementary DNA reverse transcribed from messenger RNA. The spectrum of cDNA concentrations, the expression profile, is determined using a DNA microarray. Although this approach is valuable for research, a simpler scheme that would give answers on a shorter time-scale for clinical applications is needed. An Adleman DNA self-assembly computer that would use cDNA as input might be ideal for clinical cell discrimination and a neural network architecture would be appropriate for making the necessary classifications. Preliminary experimental results suggest that expression profiling should be feasible using a DNA neural network that acts directly on cDNA.
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http://dx.doi.org/10.1016/s0167-7799(01)01915-1 | DOI Listing |
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