Artificial neural network prediction of antisense oligodeoxynucleotide activity.

ABSTRACT: An mRNA transcript contains many potential antisense oligodeoxynucleotide target sites. Identification of the most efficacious targets remains an important and challenging problem. Building on separate work that revealed a strong correlation between the inclusion of short sequence motifs and the activity level of an oligo, we have developed a predictive artificial neural network system for mapping tetranucleotide motif content to antisense oligo activity. Trained for high-specificity prediction, the system has been cross-validated against a database of 348 oligos from the literature and a larger proprietary database of 908 oligos. In cross- validation tests the system identified effective oligos (i.e. oligos capable of reducing target mRNA expression to <25% that of the control) with 53% a

SUBMITTER: Giddings MC 

PROVIDER: S-EPMC140555 | biostudies-literature | 2002 Oct

REPOSITORIES: biostudies-literature