Predicting Missing and Spurious Protein-Protein Interactions Using Graph Embeddings on GO Annotation Graph

Xiaoshi Zhong; Jagath C. Rajapakse

doi:10.1109/BIBM47256.2019.8983323

Predicting Missing and Spurious Protein-Protein Interactions Using Graph Embeddings on GO Annotation Graph

Xiaoshi Zhong
, Jagath C. Rajapakse

Nanyang Technological University

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

4 Citations (Scopus)

Abstract

Protein-protein interaction (PPI) prediction is a key step towards many bioinformatics applications including prediction of protein functions and drug-disease interactions. However, previous research on PPI prediction rarely considered missing and spurious interactions in PPI networks. To address these two issues, we define two corresponding tasks, namely missing PPI prediction and spurious PPI prediction, and propose a novel method that employs graph embeddings to learn vector representations from constructed Gene Ontology (GO) annotation graphs. Our method leverages the information from both term-term relations among GO terms and term-protein annotations between GO terms and proteins, and preserves properties of both local and global structural information of the GO annotation graph. We compare our method with methods based on information content and on word embeddings, using three PPI datasets from STRING database. Experimental results demonstrate that our method is more effective than those compared methods.

Original language	English
Title of host publication	Proceedings - 2019 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2019
Editors	Illhoi Yoo, Jinbo Bi, Xiaohua Tony Hu
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	1828-1835
Number of pages	8
ISBN (Electronic)	9781728118673
DOIs	https://doi.org/10.1109/BIBM47256.2019.8983323
Publication status	Published - Nov 2019
Externally published	Yes
Event	2019 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2019 - San Diego, United States Duration: 18 Nov 2019 → 21 Nov 2019

Publication series

Name	Proceedings - 2019 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2019

Conference

Conference	2019 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2019
Country/Territory	United States
City	San Diego
Period	18/11/19 → 21/11/19

UN SDGs

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

SDG 3 Good Health and Well-being

Keywords

GO annotation graph
graph embeddings
missing protein interactions
protein-protein interactions
spurious protein interactions

Access to Document

10.1109/BIBM47256.2019.8983323

Cite this

Zhong, X., & Rajapakse, J. C. (2019). Predicting Missing and Spurious Protein-Protein Interactions Using Graph Embeddings on GO Annotation Graph. In I. Yoo, J. Bi, & X. T. Hu (Eds.), Proceedings - 2019 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2019 (pp. 1828-1835). Article 8983323 (Proceedings - 2019 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2019). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/BIBM47256.2019.8983323

Zhong, Xiaoshi ; Rajapakse, Jagath C. / Predicting Missing and Spurious Protein-Protein Interactions Using Graph Embeddings on GO Annotation Graph. Proceedings - 2019 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2019. editor / Illhoi Yoo ; Jinbo Bi ; Xiaohua Tony Hu. Institute of Electrical and Electronics Engineers Inc., 2019. pp. 1828-1835 (Proceedings - 2019 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2019).

@inproceedings{d36ee00f8e7a40aea71a5d6c20150b89,

title = "Predicting Missing and Spurious Protein-Protein Interactions Using Graph Embeddings on GO Annotation Graph",

abstract = "Protein-protein interaction (PPI) prediction is a key step towards many bioinformatics applications including prediction of protein functions and drug-disease interactions. However, previous research on PPI prediction rarely considered missing and spurious interactions in PPI networks. To address these two issues, we define two corresponding tasks, namely missing PPI prediction and spurious PPI prediction, and propose a novel method that employs graph embeddings to learn vector representations from constructed Gene Ontology (GO) annotation graphs. Our method leverages the information from both term-term relations among GO terms and term-protein annotations between GO terms and proteins, and preserves properties of both local and global structural information of the GO annotation graph. We compare our method with methods based on information content and on word embeddings, using three PPI datasets from STRING database. Experimental results demonstrate that our method is more effective than those compared methods.",

keywords = "GO annotation graph, graph embeddings, missing protein interactions, protein-protein interactions, spurious protein interactions",

author = "Xiaoshi Zhong and Rajapakse, \{Jagath C.\}",

note = "Publisher Copyright: {\textcopyright} 2019 IEEE.; 2019 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2019 ; Conference date: 18-11-2019 Through 21-11-2019",

year = "2019",

month = nov,

doi = "10.1109/BIBM47256.2019.8983323",

language = "English",

series = "Proceedings - 2019 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2019",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "1828--1835",

editor = "Illhoi Yoo and Jinbo Bi and Hu, \{Xiaohua Tony\}",

booktitle = "Proceedings - 2019 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2019",

address = "United States",

}

Zhong, X & Rajapakse, JC 2019, Predicting Missing and Spurious Protein-Protein Interactions Using Graph Embeddings on GO Annotation Graph. in I Yoo, J Bi & XT Hu (eds), Proceedings - 2019 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2019., 8983323, Proceedings - 2019 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2019, Institute of Electrical and Electronics Engineers Inc., pp. 1828-1835, 2019 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2019, San Diego, United States, 18/11/19. https://doi.org/10.1109/BIBM47256.2019.8983323

Predicting Missing and Spurious Protein-Protein Interactions Using Graph Embeddings on GO Annotation Graph. / Zhong, Xiaoshi; Rajapakse, Jagath C.
Proceedings - 2019 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2019. ed. / Illhoi Yoo; Jinbo Bi; Xiaohua Tony Hu. Institute of Electrical and Electronics Engineers Inc., 2019. p. 1828-1835 8983323 (Proceedings - 2019 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2019).

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

TY - GEN

T1 - Predicting Missing and Spurious Protein-Protein Interactions Using Graph Embeddings on GO Annotation Graph

AU - Zhong, Xiaoshi

AU - Rajapakse, Jagath C.

PY - 2019/11

Y1 - 2019/11

N2 - Protein-protein interaction (PPI) prediction is a key step towards many bioinformatics applications including prediction of protein functions and drug-disease interactions. However, previous research on PPI prediction rarely considered missing and spurious interactions in PPI networks. To address these two issues, we define two corresponding tasks, namely missing PPI prediction and spurious PPI prediction, and propose a novel method that employs graph embeddings to learn vector representations from constructed Gene Ontology (GO) annotation graphs. Our method leverages the information from both term-term relations among GO terms and term-protein annotations between GO terms and proteins, and preserves properties of both local and global structural information of the GO annotation graph. We compare our method with methods based on information content and on word embeddings, using three PPI datasets from STRING database. Experimental results demonstrate that our method is more effective than those compared methods.

AB - Protein-protein interaction (PPI) prediction is a key step towards many bioinformatics applications including prediction of protein functions and drug-disease interactions. However, previous research on PPI prediction rarely considered missing and spurious interactions in PPI networks. To address these two issues, we define two corresponding tasks, namely missing PPI prediction and spurious PPI prediction, and propose a novel method that employs graph embeddings to learn vector representations from constructed Gene Ontology (GO) annotation graphs. Our method leverages the information from both term-term relations among GO terms and term-protein annotations between GO terms and proteins, and preserves properties of both local and global structural information of the GO annotation graph. We compare our method with methods based on information content and on word embeddings, using three PPI datasets from STRING database. Experimental results demonstrate that our method is more effective than those compared methods.

KW - GO annotation graph

KW - graph embeddings

KW - missing protein interactions

KW - protein-protein interactions

KW - spurious protein interactions

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U2 - 10.1109/BIBM47256.2019.8983323

DO - 10.1109/BIBM47256.2019.8983323

M3 - Conference contribution

AN - SCOPUS:85084333611

T3 - Proceedings - 2019 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2019

SP - 1828

EP - 1835

BT - Proceedings - 2019 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2019

A2 - Yoo, Illhoi

A2 - Bi, Jinbo

A2 - Hu, Xiaohua Tony

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2019 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2019

Y2 - 18 November 2019 through 21 November 2019

ER -

Zhong X, Rajapakse JC. Predicting Missing and Spurious Protein-Protein Interactions Using Graph Embeddings on GO Annotation Graph. In Yoo I, Bi J, Hu XT, editors, Proceedings - 2019 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2019. Institute of Electrical and Electronics Engineers Inc. 2019. p. 1828-1835. 8983323. (Proceedings - 2019 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2019). doi: 10.1109/BIBM47256.2019.8983323

Predicting Missing and Spurious Protein-Protein Interactions Using Graph Embeddings on GO Annotation Graph

Abstract

Publication series

Conference

UN SDGs

Keywords

Access to Document

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