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RetroPred: A tool for prediction, classification and extraction of non-LTR retrotransposons (LINEs & SINEs) from the genome by integrating PALS, PILER, MEME and ANN
The problem of predicting non-long terminal repeats (LTR) like long interspersed nuclear elements (LINEs) and short interspersed nuclear elements (SINEs) from the DNA sequence is still an open problem in bioinformatics. To elevate the quality of annotations of LINES and SINEs an automated tool “Retr...
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Formato: | Texto |
Lenguaje: | English |
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Biomedical Informatics Publishing Group
2008
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2258426/ https://www.ncbi.nlm.nih.gov/pubmed/18317579 |
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author | Naik, Pradeep Kumar Mittal, Vinay Kumar Gupta, Sumit |
author_facet | Naik, Pradeep Kumar Mittal, Vinay Kumar Gupta, Sumit |
author_sort | Naik, Pradeep Kumar |
collection | PubMed |
description | The problem of predicting non-long terminal repeats (LTR) like long interspersed nuclear elements (LINEs) and short interspersed nuclear elements (SINEs) from the DNA sequence is still an open problem in bioinformatics. To elevate the quality of annotations of LINES and SINEs an automated tool “RetroPred” was developed. The pipeline allowed rapid and thorough annotation of non-LTR retrotransposons. The non-LTR retrotransposable elements were initially predicted by Pairwise Aligner for Long Sequences (PALS) and Parsimonious Inference of a Library of Elementary Repeats (PILER). Predicted non-LTR elements were automatically classified into LINEs and SINEs using ANN based on the position specific probability matrix (PSPM) generated by Multiple EM for Motif Elicitation (MEME). The ANN model revealed a superior model (accuracy = 78.79 ± 6.86 %, Q(pred) = 74.734 ± 17.08 %, sensitivity = 84.48 ± 6.73 %, specificity = 77.13 ± 13.39 %) using four-fold cross validation. As proof of principle, we have thoroughly annotated the location of LINEs and SINEs in rice and Arabidopsis genome using the tool and is proved to be very useful with good accuracy. Our tool is accessible at http://www.juit.ac.in/RepeatPred/home.html. |
format | Text |
id | pubmed-2258426 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2008 |
publisher | Biomedical Informatics Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-22584262008-03-03 RetroPred: A tool for prediction, classification and extraction of non-LTR retrotransposons (LINEs & SINEs) from the genome by integrating PALS, PILER, MEME and ANN Naik, Pradeep Kumar Mittal, Vinay Kumar Gupta, Sumit Bioinformation Prediction Model The problem of predicting non-long terminal repeats (LTR) like long interspersed nuclear elements (LINEs) and short interspersed nuclear elements (SINEs) from the DNA sequence is still an open problem in bioinformatics. To elevate the quality of annotations of LINES and SINEs an automated tool “RetroPred” was developed. The pipeline allowed rapid and thorough annotation of non-LTR retrotransposons. The non-LTR retrotransposable elements were initially predicted by Pairwise Aligner for Long Sequences (PALS) and Parsimonious Inference of a Library of Elementary Repeats (PILER). Predicted non-LTR elements were automatically classified into LINEs and SINEs using ANN based on the position specific probability matrix (PSPM) generated by Multiple EM for Motif Elicitation (MEME). The ANN model revealed a superior model (accuracy = 78.79 ± 6.86 %, Q(pred) = 74.734 ± 17.08 %, sensitivity = 84.48 ± 6.73 %, specificity = 77.13 ± 13.39 %) using four-fold cross validation. As proof of principle, we have thoroughly annotated the location of LINEs and SINEs in rice and Arabidopsis genome using the tool and is proved to be very useful with good accuracy. Our tool is accessible at http://www.juit.ac.in/RepeatPred/home.html. Biomedical Informatics Publishing Group 2008-01-27 /pmc/articles/PMC2258426/ /pubmed/18317579 Text en © 2008 Biomedical Informatics Publishing Group This is an open-access article, which permits unrestricted use, distribution, and reproduction in any medium, for non-commercial purposes, provided the original author and source are credited. |
spellingShingle | Prediction Model Naik, Pradeep Kumar Mittal, Vinay Kumar Gupta, Sumit RetroPred: A tool for prediction, classification and extraction of non-LTR retrotransposons (LINEs & SINEs) from the genome by integrating PALS, PILER, MEME and ANN |
title | RetroPred: A tool for prediction, classification and extraction of non-LTR retrotransposons (LINEs & SINEs) from the genome by integrating PALS, PILER, MEME and ANN |
title_full | RetroPred: A tool for prediction, classification and extraction of non-LTR retrotransposons (LINEs & SINEs) from the genome by integrating PALS, PILER, MEME and ANN |
title_fullStr | RetroPred: A tool for prediction, classification and extraction of non-LTR retrotransposons (LINEs & SINEs) from the genome by integrating PALS, PILER, MEME and ANN |
title_full_unstemmed | RetroPred: A tool for prediction, classification and extraction of non-LTR retrotransposons (LINEs & SINEs) from the genome by integrating PALS, PILER, MEME and ANN |
title_short | RetroPred: A tool for prediction, classification and extraction of non-LTR retrotransposons (LINEs & SINEs) from the genome by integrating PALS, PILER, MEME and ANN |
title_sort | retropred: a tool for prediction, classification and extraction of non-ltr retrotransposons (lines & sines) from the genome by integrating pals, piler, meme and ann |
topic | Prediction Model |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2258426/ https://www.ncbi.nlm.nih.gov/pubmed/18317579 |
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