Human absorbable microRNA prediction based on an ensemble manifold ranking model

Jiang Shu; Kevin Chiang; Dongyu Zhao; Juan Cui

doi:10.1109/BIBM.2015.7359697

Human absorbable microRNA prediction based on an ensemble manifold ranking model

Jiang Shu, Kevin Chiang, Dongyu Zhao, Juan Cui

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

4 Scopus citations

Abstract

MicroRNAs, a class of short non-coding RNAs, are able to regulate more than half of human genes and affect many fundamental biological processes. It has been long considered synthesized endogenously until very recent discoveries showing that human can absorb exogenous microRNAs from dietary resources. This finding has raised a challenge scientific question: which exogenous microRNAs can be integrated into human circulation and possibly exert functions in human? Here we present a well-designed ensemble manifold ranking model for identifying human absorbable exogenous miRNAs from 14 common dietary species. Specifically, we have analyzed 4,910 dietary microRNAs with 1,120 features derived based on the microRNA sequence and structure. In total, 70 discriminative features were selected to characterize the circulating microRNAs in human and have been used to infer the possibility of a certain exogenous microRNA getting integrated into human circulation. Finally, 461 dietary microRNAs have been identified as transportable exogenous microRNAs. To assess the performance of our ensemble model, we have validated the top predictions through a milk-feeding study. In addition, 26 microRNAs from two virus species were predicted as transportable and have been validated in two external experiments. The results demonstrate the data-driven computational model is highly promising to study transportable microRNAs while bypassing the complex mechanistic details.

Original language	English (US)
Title of host publication	Proceedings - 2015 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2015
Editors	lng. Matthieu Schapranow, Jiayu Zhou, Xiaohua Tony Hu, Bin Ma, Sanguthevar Rajasekaran, Satoru Miyano, Illhoi Yoo, Brian Pierce, Amarda Shehu, Vijay K. Gombar, Brian Chen, Vinay Pai, Jun Huan
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	295-300
Number of pages	6
ISBN (Electronic)	9781467367981
DOIs	https://doi.org/10.1109/BIBM.2015.7359697
State	Published - Dec 16 2015
Event	IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2015 - Washington, United States Duration: Nov 9 2015 → Nov 12 2015

Publication series

Name	Proceedings - 2015 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2015

Other

Other	IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2015
Country/Territory	United States
City	Washington
Period	11/9/15 → 11/12/15

Keywords

Dietary microRNAs
cross-species transportable microRNAs
ensemble manifold ranking model
feature selection
viral miRNAs

ASJC Scopus subject areas

Software
Artificial Intelligence
Health Informatics
Biomedical Engineering

Access to Document

10.1109/BIBM.2015.7359697

Cite this

Shu, J., Chiang, K., Zhao, D., & Cui, J. (2015). Human absorbable microRNA prediction based on an ensemble manifold ranking model. In L. M. Schapranow, J. Zhou, X. T. Hu, B. Ma, S. Rajasekaran, S. Miyano, I. Yoo, B. Pierce, A. Shehu, V. K. Gombar, B. Chen, V. Pai, & J. Huan (Eds.), Proceedings - 2015 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2015 (pp. 295-300). [7359697] (Proceedings - 2015 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2015). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/BIBM.2015.7359697

Human absorbable microRNA prediction based on an ensemble manifold ranking model. / Shu, Jiang; Chiang, Kevin; Zhao, Dongyu et al.

Proceedings - 2015 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2015. ed. / lng. Matthieu Schapranow; Jiayu Zhou; Xiaohua Tony Hu; Bin Ma; Sanguthevar Rajasekaran; Satoru Miyano; Illhoi Yoo; Brian Pierce; Amarda Shehu; Vijay K. Gombar; Brian Chen; Vinay Pai; Jun Huan. Institute of Electrical and Electronics Engineers Inc., 2015. p. 295-300 7359697 (Proceedings - 2015 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2015).

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

Shu, J, Chiang, K, Zhao, D & Cui, J 2015, Human absorbable microRNA prediction based on an ensemble manifold ranking model. in LM Schapranow, J Zhou, XT Hu, B Ma, S Rajasekaran, S Miyano, I Yoo, B Pierce, A Shehu, VK Gombar, B Chen, V Pai & J Huan (eds), Proceedings - 2015 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2015., 7359697, Proceedings - 2015 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2015, Institute of Electrical and Electronics Engineers Inc., pp. 295-300, IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2015, Washington, United States, 11/9/15. https://doi.org/10.1109/BIBM.2015.7359697

Shu J, Chiang K, Zhao D, Cui J. Human absorbable microRNA prediction based on an ensemble manifold ranking model. In Schapranow LM, Zhou J, Hu XT, Ma B, Rajasekaran S, Miyano S, Yoo I, Pierce B, Shehu A, Gombar VK, Chen B, Pai V, Huan J, editors, Proceedings - 2015 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2015. Institute of Electrical and Electronics Engineers Inc. 2015. p. 295-300. 7359697. (Proceedings - 2015 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2015). doi: 10.1109/BIBM.2015.7359697

Shu, Jiang ; Chiang, Kevin ; Zhao, Dongyu et al. / Human absorbable microRNA prediction based on an ensemble manifold ranking model. Proceedings - 2015 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2015. editor / lng. Matthieu Schapranow ; Jiayu Zhou ; Xiaohua Tony Hu ; Bin Ma ; Sanguthevar Rajasekaran ; Satoru Miyano ; Illhoi Yoo ; Brian Pierce ; Amarda Shehu ; Vijay K. Gombar ; Brian Chen ; Vinay Pai ; Jun Huan. Institute of Electrical and Electronics Engineers Inc., 2015. pp. 295-300 (Proceedings - 2015 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2015).

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title = "Human absorbable microRNA prediction based on an ensemble manifold ranking model",

abstract = "MicroRNAs, a class of short non-coding RNAs, are able to regulate more than half of human genes and affect many fundamental biological processes. It has been long considered synthesized endogenously until very recent discoveries showing that human can absorb exogenous microRNAs from dietary resources. This finding has raised a challenge scientific question: which exogenous microRNAs can be integrated into human circulation and possibly exert functions in human? Here we present a well-designed ensemble manifold ranking model for identifying human absorbable exogenous miRNAs from 14 common dietary species. Specifically, we have analyzed 4,910 dietary microRNAs with 1,120 features derived based on the microRNA sequence and structure. In total, 70 discriminative features were selected to characterize the circulating microRNAs in human and have been used to infer the possibility of a certain exogenous microRNA getting integrated into human circulation. Finally, 461 dietary microRNAs have been identified as transportable exogenous microRNAs. To assess the performance of our ensemble model, we have validated the top predictions through a milk-feeding study. In addition, 26 microRNAs from two virus species were predicted as transportable and have been validated in two external experiments. The results demonstrate the data-driven computational model is highly promising to study transportable microRNAs while bypassing the complex mechanistic details.",

keywords = "Dietary microRNAs, cross-species transportable microRNAs, ensemble manifold ranking model, feature selection, viral miRNAs",

author = "Jiang Shu and Kevin Chiang and Dongyu Zhao and Juan Cui",

note = "Publisher Copyright: {\textcopyright} 2015 IEEE.; IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2015 ; Conference date: 09-11-2015 Through 12-11-2015",

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doi = "10.1109/BIBM.2015.7359697",

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editor = "Schapranow, {lng. Matthieu} and Jiayu Zhou and Hu, {Xiaohua Tony} and Bin Ma and Sanguthevar Rajasekaran and Satoru Miyano and Illhoi Yoo and Brian Pierce and Amarda Shehu and Gombar, {Vijay K.} and Brian Chen and Vinay Pai and Jun Huan",

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AU - Chiang, Kevin

AU - Zhao, Dongyu

AU - Cui, Juan

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N2 - MicroRNAs, a class of short non-coding RNAs, are able to regulate more than half of human genes and affect many fundamental biological processes. It has been long considered synthesized endogenously until very recent discoveries showing that human can absorb exogenous microRNAs from dietary resources. This finding has raised a challenge scientific question: which exogenous microRNAs can be integrated into human circulation and possibly exert functions in human? Here we present a well-designed ensemble manifold ranking model for identifying human absorbable exogenous miRNAs from 14 common dietary species. Specifically, we have analyzed 4,910 dietary microRNAs with 1,120 features derived based on the microRNA sequence and structure. In total, 70 discriminative features were selected to characterize the circulating microRNAs in human and have been used to infer the possibility of a certain exogenous microRNA getting integrated into human circulation. Finally, 461 dietary microRNAs have been identified as transportable exogenous microRNAs. To assess the performance of our ensemble model, we have validated the top predictions through a milk-feeding study. In addition, 26 microRNAs from two virus species were predicted as transportable and have been validated in two external experiments. The results demonstrate the data-driven computational model is highly promising to study transportable microRNAs while bypassing the complex mechanistic details.

AB - MicroRNAs, a class of short non-coding RNAs, are able to regulate more than half of human genes and affect many fundamental biological processes. It has been long considered synthesized endogenously until very recent discoveries showing that human can absorb exogenous microRNAs from dietary resources. This finding has raised a challenge scientific question: which exogenous microRNAs can be integrated into human circulation and possibly exert functions in human? Here we present a well-designed ensemble manifold ranking model for identifying human absorbable exogenous miRNAs from 14 common dietary species. Specifically, we have analyzed 4,910 dietary microRNAs with 1,120 features derived based on the microRNA sequence and structure. In total, 70 discriminative features were selected to characterize the circulating microRNAs in human and have been used to infer the possibility of a certain exogenous microRNA getting integrated into human circulation. Finally, 461 dietary microRNAs have been identified as transportable exogenous microRNAs. To assess the performance of our ensemble model, we have validated the top predictions through a milk-feeding study. In addition, 26 microRNAs from two virus species were predicted as transportable and have been validated in two external experiments. The results demonstrate the data-driven computational model is highly promising to study transportable microRNAs while bypassing the complex mechanistic details.

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PB - Institute of Electrical and Electronics Engineers Inc.

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ER -

Human absorbable microRNA prediction based on an ensemble manifold ranking model

Abstract

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Keywords

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