Weighted network-based inference of human microRNA-disease associations

Qinghua Jiang; Yangyang Hao; Guohua Wang; Tianjiao Zhang; Yadong Wang

doi:10.1109/FCST.2010.18

Weighted network-based inference of human microRNA-disease associations

Qinghua Jiang^*
, Yangyang Hao
, Guohua Wang
, Tianjiao Zhang
, Yadong Wang

^*Corresponding author for this work

School of Computer Science and Technology, Harbin Institute of Technology

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

19 Scopus citations

Abstract

The identification of disease microRNAs is vital for understanding the pathogenesis of diseases at the molecular level, and is critical for designing specific molecular tools for diagnosis, treatment and prevention. However, one major issue in microRNA studies is the lack of bioinformatics methods to accurately predict microRNA-disease associations. Herein, we proposed an approach to infer microRNA-disease associations based on a weighted network. We tested our method on benchmark dataset documented in the miR2Disease, a database system we developed previously for collecting experimentally verified microRNA-disease associations, and achieved an area under the ROC up to 0.80. The method described here presents a promising approach to infer new potential microRNA-disease associations, which will provide testable hypotheses to guide future biological experiments and contribute to the identification of true disease microRNAs.

Original language	English
Title of host publication	Proceedings - 5th International Conference on Frontier of Computer Science and Technology, FCST 2010
Pages	431-435
Number of pages	5
DOIs	https://doi.org/10.1109/FCST.2010.18
State	Published - 2010
Externally published	Yes
Event	5th International Conference on Frontier of Computer Science and Technology, FCST 2010 - Changchun, China Duration: 18 Aug 2010 → 22 Aug 2010

Publication series

Name	Proceedings - 5th International Conference on Frontier of Computer Science and Technology, FCST 2010

Conference

Conference	5th International Conference on Frontier of Computer Science and Technology, FCST 2010
Country/Territory	China
City	Changchun
Period	18/08/10 → 22/08/10

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

Keywords

Biological network
Concordance score
Disease microrna
Phenotype similarity

Access to Document

10.1109/FCST.2010.18

Cite this

Jiang, Q., Hao, Y., Wang, G., Zhang, T., & Wang, Y. (2010). Weighted network-based inference of human microRNA-disease associations. In Proceedings - 5th International Conference on Frontier of Computer Science and Technology, FCST 2010 (pp. 431-435). Article 5575915 (Proceedings - 5th International Conference on Frontier of Computer Science and Technology, FCST 2010). https://doi.org/10.1109/FCST.2010.18

@inproceedings{f8bc9ff6ca134d2ab376bf80e67e556e,

title = "Weighted network-based inference of human microRNA-disease associations",

abstract = "The identification of disease microRNAs is vital for understanding the pathogenesis of diseases at the molecular level, and is critical for designing specific molecular tools for diagnosis, treatment and prevention. However, one major issue in microRNA studies is the lack of bioinformatics methods to accurately predict microRNA-disease associations. Herein, we proposed an approach to infer microRNA-disease associations based on a weighted network. We tested our method on benchmark dataset documented in the miR2Disease, a database system we developed previously for collecting experimentally verified microRNA-disease associations, and achieved an area under the ROC up to 0.80. The method described here presents a promising approach to infer new potential microRNA-disease associations, which will provide testable hypotheses to guide future biological experiments and contribute to the identification of true disease microRNAs.",

keywords = "Biological network, Concordance score, Disease microrna, Phenotype similarity",

author = "Qinghua Jiang and Yangyang Hao and Guohua Wang and Tianjiao Zhang and Yadong Wang",

year = "2010",

doi = "10.1109/FCST.2010.18",

language = "英语",

isbn = "9780769541396",

series = "Proceedings - 5th International Conference on Frontier of Computer Science and Technology, FCST 2010",

pages = "431--435",

booktitle = "Proceedings - 5th International Conference on Frontier of Computer Science and Technology, FCST 2010",

note = "5th International Conference on Frontier of Computer Science and Technology, FCST 2010 ; Conference date: 18-08-2010 Through 22-08-2010",

}

Jiang, Q, Hao, Y, Wang, G, Zhang, T & Wang, Y 2010, Weighted network-based inference of human microRNA-disease associations. in Proceedings - 5th International Conference on Frontier of Computer Science and Technology, FCST 2010., 5575915, Proceedings - 5th International Conference on Frontier of Computer Science and Technology, FCST 2010, pp. 431-435, 5th International Conference on Frontier of Computer Science and Technology, FCST 2010, Changchun, China, 18/08/10. https://doi.org/10.1109/FCST.2010.18

Weighted network-based inference of human microRNA-disease associations. / Jiang, Qinghua; Hao, Yangyang; Wang, Guohua et al.
Proceedings - 5th International Conference on Frontier of Computer Science and Technology, FCST 2010. 2010. p. 431-435 5575915 (Proceedings - 5th International Conference on Frontier of Computer Science and Technology, FCST 2010).

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

TY - GEN

T1 - Weighted network-based inference of human microRNA-disease associations

AU - Jiang, Qinghua

AU - Hao, Yangyang

AU - Wang, Guohua

AU - Zhang, Tianjiao

AU - Wang, Yadong

PY - 2010

Y1 - 2010

N2 - The identification of disease microRNAs is vital for understanding the pathogenesis of diseases at the molecular level, and is critical for designing specific molecular tools for diagnosis, treatment and prevention. However, one major issue in microRNA studies is the lack of bioinformatics methods to accurately predict microRNA-disease associations. Herein, we proposed an approach to infer microRNA-disease associations based on a weighted network. We tested our method on benchmark dataset documented in the miR2Disease, a database system we developed previously for collecting experimentally verified microRNA-disease associations, and achieved an area under the ROC up to 0.80. The method described here presents a promising approach to infer new potential microRNA-disease associations, which will provide testable hypotheses to guide future biological experiments and contribute to the identification of true disease microRNAs.

AB - The identification of disease microRNAs is vital for understanding the pathogenesis of diseases at the molecular level, and is critical for designing specific molecular tools for diagnosis, treatment and prevention. However, one major issue in microRNA studies is the lack of bioinformatics methods to accurately predict microRNA-disease associations. Herein, we proposed an approach to infer microRNA-disease associations based on a weighted network. We tested our method on benchmark dataset documented in the miR2Disease, a database system we developed previously for collecting experimentally verified microRNA-disease associations, and achieved an area under the ROC up to 0.80. The method described here presents a promising approach to infer new potential microRNA-disease associations, which will provide testable hypotheses to guide future biological experiments and contribute to the identification of true disease microRNAs.

KW - Biological network

KW - Concordance score

KW - Disease microrna

KW - Phenotype similarity

UR - https://www.scopus.com/pages/publications/77957909319

U2 - 10.1109/FCST.2010.18

DO - 10.1109/FCST.2010.18

M3 - 会议稿件

AN - SCOPUS:77957909319

SN - 9780769541396

T3 - Proceedings - 5th International Conference on Frontier of Computer Science and Technology, FCST 2010

SP - 431

EP - 435

BT - Proceedings - 5th International Conference on Frontier of Computer Science and Technology, FCST 2010

T2 - 5th International Conference on Frontier of Computer Science and Technology, FCST 2010

Y2 - 18 August 2010 through 22 August 2010

ER -

Jiang Q, Hao Y, Wang G, Zhang T, Wang Y. Weighted network-based inference of human microRNA-disease associations. In Proceedings - 5th International Conference on Frontier of Computer Science and Technology, FCST 2010. 2010. p. 431-435. 5575915. (Proceedings - 5th International Conference on Frontier of Computer Science and Technology, FCST 2010). doi: 10.1109/FCST.2010.18

Weighted network-based inference of human microRNA-disease associations

Abstract

Publication series

Conference

UN SDGs

Keywords

Access to Document

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