A bayesian decision fusion approach for microRNA target prediction

Dong Yue, Hui Liu, Ming Zhu Lu, Philip Chen, Yidong Chen, Yufei Huang

Resultado de la investigación: Conference contribution

5 Citas (Scopus)

Resumen

MicroRNAs (miRNAs) are 19-25 nucleotides non-coding RNAs known to have important post-transcriptional regulatory functions. The computational target prediction algorithm is vital to effective experimental testing. However, since different existing algorithms rely on different features and classifiers, there is a poor agreement among the results of different algorithms. To benefit from the advantages of different algorithms, we proposed an algorithm called BCmicrO that combines the prediction of different algorithms with Bayesian Network. BCmicrO was evaluated using the training data and the proteomic data. The results show that BCmicrO improves both the sensitivity and the specificity of each individual algorithm.

Idioma originalEnglish (US)
Título de la publicación alojada2010 ACM International Conference on Bioinformatics and Computational Biology, ACM-BCB 2010
Páginas214-221
Número de páginas8
DOI
EstadoPublished - 2010
Evento2010 ACM International Conference on Bioinformatics and Computational Biology, ACM-BCB 2010 - Niagara Falls, NY, United States
Duración: ago. 2 2010ago. 4 2010

Serie de la publicación

Nombre2010 ACM International Conference on Bioinformatics and Computational Biology, ACM-BCB 2010

Other

Other2010 ACM International Conference on Bioinformatics and Computational Biology, ACM-BCB 2010
País/TerritorioUnited States
CiudadNiagara Falls, NY
Período8/2/108/4/10

ASJC Scopus subject areas

  • Biomedical Engineering
  • Health Information Management

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