Constructing Node Embeddings for Human Phenotype Ontology to Assist Phenotypic Similarity Measurement

Feichen Shen; Sijia Liu; Yanshan Wang; Liwei Wang; Andrew Wen; Andrew H. Limper; Hongfang Liu

doi:10.1109/ICHI-W.2018.00011

Constructing Node Embeddings for Human Phenotype Ontology to Assist Phenotypic Similarity Measurement

Feichen Shen, Sijia Liu, Yanshan Wang, Liwei Wang, Andrew Wen, Andrew H. Limper, Hongfang Liu

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

6 Scopus citations

Abstract

The Human Phenotype Ontology (HPO) was developed to be a semantically computable vocabulary that captures the phenotypic abnormalities found in human diseases discovered through biomedical research. Usage of this ontology facilitates the translation between genotype and phenotype. Many studies have been conducted to accelerate the implementation of precision medicine into clinical practice by utilizing the informative contents provided in the HPO. No work, however, has been done in constructing a distributed representation for nodes in HPO to provide a deep insight of phenotypic similarities by analyzing its graph structure. Node2vec is a model for generating node embeddings based on large networks. In this study, we constructed node embeddings for the HPO leveraging node2vec to assist phenotypic similarity measurement. A downstream application on link prediction driven by HPO embedding achieved 0.81 ROAUC and 0.75 F-measure. A use case study was conducted on idiopathic pulmonary fibrosis (IPF) and we demonstrated the potential possibility of using HPO embeddings in assisting phenotypic similarity measurement.

Original language	English (US)
Title of host publication	Proceedings - 2018 IEEE International Conference on Healthcare Informatics Workshops, ICHI-W 2018
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	29-33
Number of pages	5
ISBN (Electronic)	9781538667774
DOIs	https://doi.org/10.1109/ICHI-W.2018.00011
State	Published - Jul 16 2018
Event	6th IEEE International Conference on Healthcare Informatics Workshops, ICHI-W 2018 - New York, United States Duration: Jun 4 2018 → Jun 7 2018

Publication series

Name	Proceedings - 2018 IEEE International Conference on Healthcare Informatics Workshops, ICHI-W 2018

Other

Other	6th IEEE International Conference on Healthcare Informatics Workshops, ICHI-W 2018
Country/Territory	United States
City	New York
Period	6/4/18 → 6/7/18

Keywords

Human Phenotype Ontology
Node embeddings
Phenotypic similarity

ASJC Scopus subject areas

Information Systems and Management
Health Informatics

Access to Document

10.1109/ICHI-W.2018.00011

Cite this

Shen, F., Liu, S., Wang, Y., Wang, L., Wen, A., Limper, A. H., & Liu, H. (2018). Constructing Node Embeddings for Human Phenotype Ontology to Assist Phenotypic Similarity Measurement. In Proceedings - 2018 IEEE International Conference on Healthcare Informatics Workshops, ICHI-W 2018 (pp. 29-33). Article 8411677 (Proceedings - 2018 IEEE International Conference on Healthcare Informatics Workshops, ICHI-W 2018). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICHI-W.2018.00011

Constructing Node Embeddings for Human Phenotype Ontology to Assist Phenotypic Similarity Measurement. / Shen, Feichen; Liu, Sijia; Wang, Yanshan et al.
Proceedings - 2018 IEEE International Conference on Healthcare Informatics Workshops, ICHI-W 2018. Institute of Electrical and Electronics Engineers Inc., 2018. p. 29-33 8411677 (Proceedings - 2018 IEEE International Conference on Healthcare Informatics Workshops, ICHI-W 2018).

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

Shen, F, Liu, S, Wang, Y, Wang, L, Wen, A, Limper, AH & Liu, H 2018, Constructing Node Embeddings for Human Phenotype Ontology to Assist Phenotypic Similarity Measurement. in Proceedings - 2018 IEEE International Conference on Healthcare Informatics Workshops, ICHI-W 2018., 8411677, Proceedings - 2018 IEEE International Conference on Healthcare Informatics Workshops, ICHI-W 2018, Institute of Electrical and Electronics Engineers Inc., pp. 29-33, 6th IEEE International Conference on Healthcare Informatics Workshops, ICHI-W 2018, New York, United States, 6/4/18. https://doi.org/10.1109/ICHI-W.2018.00011

Shen F, Liu S, Wang Y, Wang L, Wen A, Limper AH et al. Constructing Node Embeddings for Human Phenotype Ontology to Assist Phenotypic Similarity Measurement. In Proceedings - 2018 IEEE International Conference on Healthcare Informatics Workshops, ICHI-W 2018. Institute of Electrical and Electronics Engineers Inc. 2018. p. 29-33. 8411677. (Proceedings - 2018 IEEE International Conference on Healthcare Informatics Workshops, ICHI-W 2018). doi: 10.1109/ICHI-W.2018.00011

Shen, Feichen ; Liu, Sijia ; Wang, Yanshan et al. / Constructing Node Embeddings for Human Phenotype Ontology to Assist Phenotypic Similarity Measurement. Proceedings - 2018 IEEE International Conference on Healthcare Informatics Workshops, ICHI-W 2018. Institute of Electrical and Electronics Engineers Inc., 2018. pp. 29-33 (Proceedings - 2018 IEEE International Conference on Healthcare Informatics Workshops, ICHI-W 2018).

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abstract = "The Human Phenotype Ontology (HPO) was developed to be a semantically computable vocabulary that captures the phenotypic abnormalities found in human diseases discovered through biomedical research. Usage of this ontology facilitates the translation between genotype and phenotype. Many studies have been conducted to accelerate the implementation of precision medicine into clinical practice by utilizing the informative contents provided in the HPO. No work, however, has been done in constructing a distributed representation for nodes in HPO to provide a deep insight of phenotypic similarities by analyzing its graph structure. Node2vec is a model for generating node embeddings based on large networks. In this study, we constructed node embeddings for the HPO leveraging node2vec to assist phenotypic similarity measurement. A downstream application on link prediction driven by HPO embedding achieved 0.81 ROAUC and 0.75 F-measure. A use case study was conducted on idiopathic pulmonary fibrosis (IPF) and we demonstrated the potential possibility of using HPO embeddings in assisting phenotypic similarity measurement.",

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AB - The Human Phenotype Ontology (HPO) was developed to be a semantically computable vocabulary that captures the phenotypic abnormalities found in human diseases discovered through biomedical research. Usage of this ontology facilitates the translation between genotype and phenotype. Many studies have been conducted to accelerate the implementation of precision medicine into clinical practice by utilizing the informative contents provided in the HPO. No work, however, has been done in constructing a distributed representation for nodes in HPO to provide a deep insight of phenotypic similarities by analyzing its graph structure. Node2vec is a model for generating node embeddings based on large networks. In this study, we constructed node embeddings for the HPO leveraging node2vec to assist phenotypic similarity measurement. A downstream application on link prediction driven by HPO embedding achieved 0.81 ROAUC and 0.75 F-measure. A use case study was conducted on idiopathic pulmonary fibrosis (IPF) and we demonstrated the potential possibility of using HPO embeddings in assisting phenotypic similarity measurement.

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Constructing Node Embeddings for Human Phenotype Ontology to Assist Phenotypic Similarity Measurement

Abstract

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Keywords

ASJC Scopus subject areas

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