Cargando…

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...

Descripción completa

Detalles Bibliográficos
Autores principales: Lu, Jun, Luo, Liaofu
Formato: Texto
Lenguaje:English
Publicado: Biomedical Informatics Publishing Group 2008
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2374378/
https://www.ncbi.nlm.nih.gov/pubmed/18478087
_version_ 1782154439363133440
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