Cargando…

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

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...

Descripción completa

Detalles Bibliográficos
Autores principales: Liu, Chun-Chi, Lin, Chin-Chung, Li, Ker-Chau, Chen, Wen-Shyen E, Chen, Jiun-Ching, Yang, Ming-Te, Yang, Pan-Chyr, Chang, Pei-Chun, Chen, Jeremy JW
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2007
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1892811/
https://www.ncbi.nlm.nih.gov/pubmed/17518996
http://dx.doi.org/10.1186/1471-2105-8-164
_version_ 1782133859447472128
author Liu, Chun-Chi
Lin, Chin-Chung
Li, Ker-Chau
Chen, Wen-Shyen E
Chen, Jiun-Ching
Yang, Ming-Te
Yang, Pan-Chyr
Chang, Pei-Chun
Chen, Jeremy JW
author_facet Liu, Chun-Chi
Lin, Chin-Chung
Li, Ker-Chau
Chen, Wen-Shyen E
Chen, Jiun-Ching
Yang, Ming-Te
Yang, Pan-Chyr
Chang, Pei-Chun
Chen, Jeremy JW
author_sort Liu, Chun-Chi
collection PubMed
description 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 the specific oligos with high efficiency, and these oligos were subsequently verified by BLAST. To improve the prediction performance, the ANN over-fitting issue was avoided by early stopping with the best observed error and a k-fold validation was also applied. The performance of the IAB algorithm was about 5.2, 7.1, and 6.7 times faster than the BLAST search without ANN for experimental results of 70-mer, 50-mer, and 25-mer specific oligos, respectively. In addition, the results of polymerase chain reactions showed that the primers predicted by the IAB algorithm could specifically amplify the corresponding genes. The IAB algorithm has been integrated into a previously published comprehensive web server to support microarray analysis and genome-wide iterative enrichment analysis, through which users can identify a group of desired genes and then discover the specific oligos of these genes. CONCLUSION: The IAB algorithm has been developed to construct SpecificDB, a web server that provides a specific and valid oligo database of the probe, siRNA, and primer design for the human genome. We also demonstrate the ability of the IAB algorithm to predict specific oligos through polymerase chain reaction experiments. SpecificDB provides comprehensive information and a user-friendly interface.
format Text
id pubmed-1892811
institution National Center for Biotechnology Information
language English
publishDate 2007
publisher BioMed Central
record_format MEDLINE/PubMed
spelling pubmed-18928112007-06-19 Genome-wide identification of specific oligonucleotides using artificial neural network and computational genomic analysis Liu, Chun-Chi Lin, Chin-Chung Li, Ker-Chau Chen, Wen-Shyen E Chen, Jiun-Ching Yang, Ming-Te Yang, Pan-Chyr Chang, Pei-Chun Chen, Jeremy JW BMC Bioinformatics Methodology Article 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 the specific oligos with high efficiency, and these oligos were subsequently verified by BLAST. To improve the prediction performance, the ANN over-fitting issue was avoided by early stopping with the best observed error and a k-fold validation was also applied. The performance of the IAB algorithm was about 5.2, 7.1, and 6.7 times faster than the BLAST search without ANN for experimental results of 70-mer, 50-mer, and 25-mer specific oligos, respectively. In addition, the results of polymerase chain reactions showed that the primers predicted by the IAB algorithm could specifically amplify the corresponding genes. The IAB algorithm has been integrated into a previously published comprehensive web server to support microarray analysis and genome-wide iterative enrichment analysis, through which users can identify a group of desired genes and then discover the specific oligos of these genes. CONCLUSION: The IAB algorithm has been developed to construct SpecificDB, a web server that provides a specific and valid oligo database of the probe, siRNA, and primer design for the human genome. We also demonstrate the ability of the IAB algorithm to predict specific oligos through polymerase chain reaction experiments. SpecificDB provides comprehensive information and a user-friendly interface. BioMed Central 2007-05-22 /pmc/articles/PMC1892811/ /pubmed/17518996 http://dx.doi.org/10.1186/1471-2105-8-164 Text en Copyright © 2007 Liu et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( (http://creativecommons.org/licenses/by/2.0) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Methodology Article
Liu, Chun-Chi
Lin, Chin-Chung
Li, Ker-Chau
Chen, Wen-Shyen E
Chen, Jiun-Ching
Yang, Ming-Te
Yang, Pan-Chyr
Chang, Pei-Chun
Chen, Jeremy JW
Genome-wide identification of specific oligonucleotides using artificial neural network and computational genomic analysis
title Genome-wide identification of specific oligonucleotides using artificial neural network and computational genomic analysis
title_full Genome-wide identification of specific oligonucleotides using artificial neural network and computational genomic analysis
title_fullStr Genome-wide identification of specific oligonucleotides using artificial neural network and computational genomic analysis
title_full_unstemmed Genome-wide identification of specific oligonucleotides using artificial neural network and computational genomic analysis
title_short Genome-wide identification of specific oligonucleotides using artificial neural network and computational genomic analysis
title_sort genome-wide identification of specific oligonucleotides using artificial neural network and computational genomic analysis
topic Methodology Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1892811/
https://www.ncbi.nlm.nih.gov/pubmed/17518996
http://dx.doi.org/10.1186/1471-2105-8-164
work_keys_str_mv AT liuchunchi genomewideidentificationofspecificoligonucleotidesusingartificialneuralnetworkandcomputationalgenomicanalysis
AT linchinchung genomewideidentificationofspecificoligonucleotidesusingartificialneuralnetworkandcomputationalgenomicanalysis
AT likerchau genomewideidentificationofspecificoligonucleotidesusingartificialneuralnetworkandcomputationalgenomicanalysis
AT chenwenshyene genomewideidentificationofspecificoligonucleotidesusingartificialneuralnetworkandcomputationalgenomicanalysis
AT chenjiunching genomewideidentificationofspecificoligonucleotidesusingartificialneuralnetworkandcomputationalgenomicanalysis
AT yangmingte genomewideidentificationofspecificoligonucleotidesusingartificialneuralnetworkandcomputationalgenomicanalysis
AT yangpanchyr genomewideidentificationofspecificoligonucleotidesusingartificialneuralnetworkandcomputationalgenomicanalysis
AT changpeichun genomewideidentificationofspecificoligonucleotidesusingartificialneuralnetworkandcomputationalgenomicanalysis
AT chenjeremyjw genomewideidentificationofspecificoligonucleotidesusingartificialneuralnetworkandcomputationalgenomicanalysis