A comprehensive study of a svm-based mirna target prediction algorithm

Hui Liu; Dong Yue; Yidong Chen; Yufei Huang

doi:10.1109/GENSIPS.2009.5174346

A comprehensive study of a svm-based mirna target prediction algorithm

Hui Liu, Dong Yue, Yidong Chen, Yufei Huang

Producción científica: Conference contribution

Resumen

MicroRNAs are single-stranded non-coding RNAs that play important regulatory roles in many biological processes and diseases. Identifying miRNA regulatory targets is paramount in elucidating its function. We carried out a comprehensive study of a new SYM-based target prediction algorithm called SYMicrO in this paper. The training data set is carefully derived from the most up-to-date collection of verified target s and multiple microarray data sets. Several varieties of feature design and selection schemes are investigated. The prediction results are compared with most of the existing algorithms, which show improved sensitivity and specificity of this two-stage SYM algorithm.

Idioma original	English (US)
Título de la publicación alojada	2009 IEEE International Workshop on Genomic Signal Processing and Statistics, GENSIPS 2009
DOI	https://doi.org/10.1109/GENSIPS.2009.5174346
Estado	Published - 2009
Evento	2009 IEEE International Workshop on Genomic Signal Processing and Statistics, GENSIPS 2009 - Minneapolis, MN, United States Duración: may 17 2009 → may 21 2009

Serie de la publicación

Nombre	2009 IEEE International Workshop on Genomic Signal Processing and Statistics, GENSIPS 2009

Other

Other	2009 IEEE International Workshop on Genomic Signal Processing and Statistics, GENSIPS 2009
País/Territorio	United States
Ciudad	Minneapolis, MN
Período	5/17/09 → 5/21/09

ASJC Scopus subject areas

Molecular Biology
Computational Theory and Mathematics
Computer Vision and Pattern Recognition
Biomedical Engineering

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10.1109/GENSIPS.2009.5174346

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Liu, H., Yue, D., Chen, Y., & Huang, Y. (2009). A comprehensive study of a svm-based mirna target prediction algorithm. En 2009 IEEE International Workshop on Genomic Signal Processing and Statistics, GENSIPS 2009 Artículo 5174346 (2009 IEEE International Workshop on Genomic Signal Processing and Statistics, GENSIPS 2009). https://doi.org/10.1109/GENSIPS.2009.5174346

Liu, H, Yue, D, Chen, Y & Huang, Y 2009, A comprehensive study of a svm-based mirna target prediction algorithm. En 2009 IEEE International Workshop on Genomic Signal Processing and Statistics, GENSIPS 2009., 5174346, 2009 IEEE International Workshop on Genomic Signal Processing and Statistics, GENSIPS 2009, 2009 IEEE International Workshop on Genomic Signal Processing and Statistics, GENSIPS 2009, Minneapolis, MN, United States, 5/17/09. https://doi.org/10.1109/GENSIPS.2009.5174346

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abstract = "MicroRNAs are single-stranded non-coding RNAs that play important regulatory roles in many biological processes and diseases. Identifying miRNA regulatory targets is paramount in elucidating its function. We carried out a comprehensive study of a new SYM-based target prediction algorithm called SYMicrO in this paper. The training data set is carefully derived from the most up-to-date collection of verified target s and multiple microarray data sets. Several varieties of feature design and selection schemes are investigated. The prediction results are compared with most of the existing algorithms, which show improved sensitivity and specificity of this two-stage SYM algorithm.",

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AB - MicroRNAs are single-stranded non-coding RNAs that play important regulatory roles in many biological processes and diseases. Identifying miRNA regulatory targets is paramount in elucidating its function. We carried out a comprehensive study of a new SYM-based target prediction algorithm called SYMicrO in this paper. The training data set is carefully derived from the most up-to-date collection of verified target s and multiple microarray data sets. Several varieties of feature design and selection schemes are investigated. The prediction results are compared with most of the existing algorithms, which show improved sensitivity and specificity of this two-stage SYM algorithm.

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A comprehensive study of a svm-based mirna target prediction algorithm

Resumen

Serie de la publicación

Other

ASJC Scopus subject areas

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