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Prediction for human transcription start site using diversity measure with quadratic discriminant
The accurate identification of promoter regions and transcription start sites is a challenge to the construction of human transcription regulation networks. Thus, an efficient prediction method based on theoretical formulation is necessary for this purpose. We used the method of increment diversity...
Autores principales: | , |
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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/PMC2374378/ https://www.ncbi.nlm.nih.gov/pubmed/18478087 |
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author | Lu, Jun Luo, Liaofu |
author_facet | Lu, Jun Luo, Liaofu |
author_sort | Lu, Jun |
collection | PubMed |
description | The accurate identification of promoter regions and transcription start sites is a challenge to the construction of human transcription regulation networks. Thus, an efficient prediction method based on theoretical formulation is necessary for this purpose. We used the method of increment diversity with quadratic discriminant analysis (IDQD) to predict transcription start sites (TSS). The method produced sensitivity and positive predictive value of more than 65% with positives to negatives ratio of 1:58. The performance evaluation using Receiver Operator Characteristics (ROC) showed an auROC (area under ROC) of greater than 96%. The evaluation by Precision Recall Curves (PRC) showed an auPRC (area under PRC) of about 26% for positives to negatives ratio of 1:679 and about 64% for positives to negatives ratio of 1:113. The results documented in this approach are either better or comparable to other known methods. |
format | Text |
id | pubmed-2374378 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2008 |
publisher | Biomedical Informatics Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-23743782008-05-13 Prediction for human transcription start site using diversity measure with quadratic discriminant Lu, Jun Luo, Liaofu Bioinformation Prediction Model The accurate identification of promoter regions and transcription start sites is a challenge to the construction of human transcription regulation networks. Thus, an efficient prediction method based on theoretical formulation is necessary for this purpose. We used the method of increment diversity with quadratic discriminant analysis (IDQD) to predict transcription start sites (TSS). The method produced sensitivity and positive predictive value of more than 65% with positives to negatives ratio of 1:58. The performance evaluation using Receiver Operator Characteristics (ROC) showed an auROC (area under ROC) of greater than 96%. The evaluation by Precision Recall Curves (PRC) showed an auPRC (area under PRC) of about 26% for positives to negatives ratio of 1:679 and about 64% for positives to negatives ratio of 1:113. The results documented in this approach are either better or comparable to other known methods. Biomedical Informatics Publishing Group 2008-04-28 /pmc/articles/PMC2374378/ /pubmed/18478087 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 Lu, Jun Luo, Liaofu Prediction for human transcription start site using diversity measure with quadratic discriminant |
title | Prediction for human transcription start site using diversity measure with quadratic discriminant |
title_full | Prediction for human transcription start site using diversity measure with quadratic discriminant |
title_fullStr | Prediction for human transcription start site using diversity measure with quadratic discriminant |
title_full_unstemmed | Prediction for human transcription start site using diversity measure with quadratic discriminant |
title_short | Prediction for human transcription start site using diversity measure with quadratic discriminant |
title_sort | prediction for human transcription start site using diversity measure with quadratic discriminant |
topic | Prediction Model |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2374378/ https://www.ncbi.nlm.nih.gov/pubmed/18478087 |
work_keys_str_mv | AT lujun predictionforhumantranscriptionstartsiteusingdiversitymeasurewithquadraticdiscriminant AT luoliaofu predictionforhumantranscriptionstartsiteusingdiversitymeasurewithquadraticdiscriminant |