Evaluation of gel-pad oligonucleotide microarray technology by using artificial neural networks.

ABSTRACT: Past studies have suggested that thermal dissociation analysis of nucleic acids hybridized to DNA microarrays would improve discrimination among duplex types by scanning through a broad range of stringency conditions. To more fully constrain the utility of this approach using a previously described gel-pad microarray format, artificial neural networks (NNs) were trained to recognize noisy or low-quality data, as might derive from nonspecific fluorescence, poor hybridization, or compromised data collection. The NNs were trained to classify dissociation profiles (melts) into groups based on selected characteristics (e.g., initial signal intensity, area under the curve) using a data set of 21,044 profiles derived from 186 probes hybridized to a study set of RNA extracted from 32 microbes comm

SUBMITTER: Pozhitkov A 

PROVIDER: S-EPMC1317365 | biostudies-literature | 2005 Dec

REPOSITORIES: biostudies-literature