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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...

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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
Descripción
Sumario: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.