Genome-wide identification of specific oligonucleotides using artificial neural network and computational genomic analysis.

ABSTRACT:

Background

Genome-wide identification of specific oligonucleotides (oligos) is a computationally-intensive task and is a requirement for designing microarray probes, primers, and siRNAs. An artificial neural network (ANN) is a machine learning technique that can effectively process complex and high noise data. Here, ANNs are applied to process the unique subsequence distribution for prediction of specific oligos.

Results

We present a novel and efficient algorithm, named the integration of ANN and BLAST (IAB) algorithm, to identify specific oligos. We establish the unique marker database for human and rat gene index databases using the hash table algorithm. We then create the input vectors, via the unique marker database, to train and test the ANN. The trained ANN predicted t

SUBMITTER: Liu CC 

PROVIDER: S-EPMC1892811 | biostudies-literature | 2007 May

REPOSITORIES: biostudies-literature