CpGPAP: CpG island predictor analysis platform
<p>Abstract</p> <p>Background</p> <p>Genomic islands play an important role in medical, methylation and biological studies. To explore the region, we propose a CpG islands prediction analysis platform for genome sequence exploration (CpGPAP).</p> <p>Results&...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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BMC
2012-03-01
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| Series: | BMC Genetics |
| Online Access: | http://www.biomedcentral.com/1471-2156/13/13 |
| _version_ | 1818572254766694400 |
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| author | Chuang Li-Yeh Yang Cheng-Huei Lin Ming-Cheng Yang Cheng-Hong |
| author_facet | Chuang Li-Yeh Yang Cheng-Huei Lin Ming-Cheng Yang Cheng-Hong |
| author_sort | Chuang Li-Yeh |
| collection | DOAJ |
| description | <p>Abstract</p> <p>Background</p> <p>Genomic islands play an important role in medical, methylation and biological studies. To explore the region, we propose a CpG islands prediction analysis platform for genome sequence exploration (CpGPAP).</p> <p>Results</p> <p>CpGPAP is a web-based application that provides a user-friendly interface for predicting CpG islands in genome sequences or in user input sequences. The prediction algorithms supported in CpGPAP include complementary particle swarm optimization (CPSO), a complementary genetic algorithm (CGA) and other methods (CpGPlot, CpGProD and CpGIS) found in the literature. The CpGPAP platform is easy to use and has three main features (1) selection of the prediction algorithm; (2) graphic visualization of results; and (3) application of related tools and dataset downloads. These features allow the user to easily view CpG island results and download the relevant island data. CpGPAP is freely available at <url>http://bio.kuas.edu.tw/CpGPAP/</url>.</p> <p>Conclusions</p> <p>The platform's supported algorithms (CPSO and CGA) provide a higher sensitivity and a higher correlation coefficient when compared to CpGPlot, CpGProD, CpGIS, and CpGcluster over an entire chromosome.</p> |
| first_indexed | 2024-12-14T18:54:38Z |
| format | Article |
| id | doaj.art-659a57a4d9c34b17ac44f23370838436 |
| institution | Directory Open Access Journal |
| issn | 1471-2156 |
| language | English |
| last_indexed | 2024-12-14T18:54:38Z |
| publishDate | 2012-03-01 |
| publisher | BMC |
| record_format | Article |
| series | BMC Genetics |
| spelling | doaj.art-659a57a4d9c34b17ac44f233708384362022-12-21T22:51:07ZengBMCBMC Genetics1471-21562012-03-011311310.1186/1471-2156-13-13CpGPAP: CpG island predictor analysis platformChuang Li-YehYang Cheng-HueiLin Ming-ChengYang Cheng-Hong<p>Abstract</p> <p>Background</p> <p>Genomic islands play an important role in medical, methylation and biological studies. To explore the region, we propose a CpG islands prediction analysis platform for genome sequence exploration (CpGPAP).</p> <p>Results</p> <p>CpGPAP is a web-based application that provides a user-friendly interface for predicting CpG islands in genome sequences or in user input sequences. The prediction algorithms supported in CpGPAP include complementary particle swarm optimization (CPSO), a complementary genetic algorithm (CGA) and other methods (CpGPlot, CpGProD and CpGIS) found in the literature. The CpGPAP platform is easy to use and has three main features (1) selection of the prediction algorithm; (2) graphic visualization of results; and (3) application of related tools and dataset downloads. These features allow the user to easily view CpG island results and download the relevant island data. CpGPAP is freely available at <url>http://bio.kuas.edu.tw/CpGPAP/</url>.</p> <p>Conclusions</p> <p>The platform's supported algorithms (CPSO and CGA) provide a higher sensitivity and a higher correlation coefficient when compared to CpGPlot, CpGProD, CpGIS, and CpGcluster over an entire chromosome.</p>http://www.biomedcentral.com/1471-2156/13/13 |
| spellingShingle | Chuang Li-Yeh Yang Cheng-Huei Lin Ming-Cheng Yang Cheng-Hong CpGPAP: CpG island predictor analysis platform BMC Genetics |
| title | CpGPAP: CpG island predictor analysis platform |
| title_full | CpGPAP: CpG island predictor analysis platform |
| title_fullStr | CpGPAP: CpG island predictor analysis platform |
| title_full_unstemmed | CpGPAP: CpG island predictor analysis platform |
| title_short | CpGPAP: CpG island predictor analysis platform |
| title_sort | cpgpap cpg island predictor analysis platform |
| url | http://www.biomedcentral.com/1471-2156/13/13 |
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