Computational prediction of microRNA regulatory pathways

Dong Yue; Yidong Chen; Shou Jiang Gao; Yufei Huang

Computational prediction of microRNA regulatory pathways

Dong Yue, Yidong Chen, Shou Jiang Gao, Yufei Huang

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

MicroRNAs (miRNAs) are known to regulate transcription and/or protein translation of hundreds of genes. Despite their importance, the functions of most human miRNAs are still poorly understood. In this paper, we proposed a SVM based algorithm - PathMicrO that elucidates the miRNA function by predicting the miRNA regulated pathways. PathMicrO combines the sequence-level target predictions with the gene expression profiling from the miRNA transfection experiments. The performance of PathMicrO is evaluated with cross-validation using a careful constructed training data and two independent testing data. Compared to other prediction algorithms, PathMicrO attains 77% more in sensitivity when false positive rate is equal to 0.21 and achieves much larger area under the receiver operating characteristic (ROC) curve.

Original language	English (US)
Title of host publication	Proceedings 2011 IEEE International Workshop on Genomic Signal Processing and Statistics, GENSIPS'11
Pages	158-161
Number of pages	4
State	Published - Dec 1 2011
Event	2011 IEEE International Workshop on Genomic Signal Processing and Statistics, GENSIPS'11 - San Antonio, TX, United States Duration: Dec 4 2011 → Dec 6 2011

Publication series

Name	Proceedings - IEEE International Workshop on Genomic Signal Processing and Statistics
ISSN (Print)	2150-3001
ISSN (Electronic)	2150-301X

Other

Other	2011 IEEE International Workshop on Genomic Signal Processing and Statistics, GENSIPS'11
Country/Territory	United States
City	San Antonio, TX
Period	12/4/11 → 12/6/11

Keywords

Function
PathmicrO
Pathway
SVM
microRNA

ASJC Scopus subject areas

Biochemistry, Genetics and Molecular Biology (miscellaneous)
Computational Theory and Mathematics
Signal Processing
Biomedical Engineering

Cite this

Computational prediction of microRNA regulatory pathways. / Yue, Dong; Chen, Yidong; Gao, Shou Jiang et al.
Proceedings 2011 IEEE International Workshop on Genomic Signal Processing and Statistics, GENSIPS'11. 2011. p. 158-161 6169469 (Proceedings - IEEE International Workshop on Genomic Signal Processing and Statistics).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Yue, D, Chen, Y, Gao, SJ & Huang, Y 2011, Computational prediction of microRNA regulatory pathways. in Proceedings 2011 IEEE International Workshop on Genomic Signal Processing and Statistics, GENSIPS'11., 6169469, Proceedings - IEEE International Workshop on Genomic Signal Processing and Statistics, pp. 158-161, 2011 IEEE International Workshop on Genomic Signal Processing and Statistics, GENSIPS'11, San Antonio, TX, United States, 12/4/11.

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title = "Computational prediction of microRNA regulatory pathways",

abstract = "MicroRNAs (miRNAs) are known to regulate transcription and/or protein translation of hundreds of genes. Despite their importance, the functions of most human miRNAs are still poorly understood. In this paper, we proposed a SVM based algorithm - PathMicrO that elucidates the miRNA function by predicting the miRNA regulated pathways. PathMicrO combines the sequence-level target predictions with the gene expression profiling from the miRNA transfection experiments. The performance of PathMicrO is evaluated with cross-validation using a careful constructed training data and two independent testing data. Compared to other prediction algorithms, PathMicrO attains 77% more in sensitivity when false positive rate is equal to 0.21 and achieves much larger area under the receiver operating characteristic (ROC) curve.",

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N2 - MicroRNAs (miRNAs) are known to regulate transcription and/or protein translation of hundreds of genes. Despite their importance, the functions of most human miRNAs are still poorly understood. In this paper, we proposed a SVM based algorithm - PathMicrO that elucidates the miRNA function by predicting the miRNA regulated pathways. PathMicrO combines the sequence-level target predictions with the gene expression profiling from the miRNA transfection experiments. The performance of PathMicrO is evaluated with cross-validation using a careful constructed training data and two independent testing data. Compared to other prediction algorithms, PathMicrO attains 77% more in sensitivity when false positive rate is equal to 0.21 and achieves much larger area under the receiver operating characteristic (ROC) curve.

AB - MicroRNAs (miRNAs) are known to regulate transcription and/or protein translation of hundreds of genes. Despite their importance, the functions of most human miRNAs are still poorly understood. In this paper, we proposed a SVM based algorithm - PathMicrO that elucidates the miRNA function by predicting the miRNA regulated pathways. PathMicrO combines the sequence-level target predictions with the gene expression profiling from the miRNA transfection experiments. The performance of PathMicrO is evaluated with cross-validation using a careful constructed training data and two independent testing data. Compared to other prediction algorithms, PathMicrO attains 77% more in sensitivity when false positive rate is equal to 0.21 and achieves much larger area under the receiver operating characteristic (ROC) curve.

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Computational prediction of microRNA regulatory pathways

Abstract

Publication series

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Keywords

ASJC Scopus subject areas

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