CODA: Integrating multi-level context-oriented directed associations for analysis of drug effects

Abstract In silico network-based methods have shown promising results in the field of drug development. Yet, most of networks used in the previous research have not included context information even though biological associations actually do appear in the specific contexts. Here, we reconstruct an a...

Full description

Bibliographic Details
Main Authors: Hasun Yu, Jinmyung Jung, Seyeol Yoon, Mijin Kwon, Sunghwa Bae, Soorin Yim, Jaehyun Lee, Seunghyun Kim, Yeeok Kang, Doheon Lee
Format: Article
Language:English
Published: Nature Publishing Group 2017-08-01
Series:Scientific Reports
Online Access:https://doi.org/10.1038/s41598-017-07448-6
id doaj-e86ff0bfc6124139b31a2f0eadf7d511
record_format Article
spelling doaj-e86ff0bfc6124139b31a2f0eadf7d5112020-12-08T00:31:54ZengNature Publishing GroupScientific Reports2045-23222017-08-017111210.1038/s41598-017-07448-6CODA: Integrating multi-level context-oriented directed associations for analysis of drug effectsHasun Yu0Jinmyung Jung1Seyeol Yoon2Mijin Kwon3Sunghwa Bae4Soorin Yim5Jaehyun Lee6Seunghyun Kim7Yeeok Kang8Doheon Lee9Department of Bio and Brain EngineeringDepartment of Bio and Brain EngineeringDepartment of Bio and Brain EngineeringDepartment of Bio and Brain EngineeringDepartment of Bio and Brain EngineeringDepartment of Bio and Brain EngineeringDepartment of Bio and Brain EngineeringDepartment of Bio and Brain EngineeringSD Genomics Co., Ltd.Department of Bio and Brain EngineeringAbstract In silico network-based methods have shown promising results in the field of drug development. Yet, most of networks used in the previous research have not included context information even though biological associations actually do appear in the specific contexts. Here, we reconstruct an anatomical context-specific network by assigning contexts to biological associations using protein expression data and scientific literature. Furthermore, we employ the context-specific network for the analysis of drug effects with a proximity measure between drug targets and diseases. Distinct from previous context-specific networks, intercellular associations and phenomic level entities such as biological processes are included in our network to represent the human body. It is observed that performances in inferring drug-disease associations are increased by adding context information and phenomic level entities. In particular, hypertension, a disease related to multiple organs and associated with several phenomic level entities, is analyzed in detail to investigate how our network facilitates the inference of drug-disease associations. Our results indicate that the inclusion of context information, intercellular associations, and phenomic level entities can contribute towards a better prediction of drug-disease associations and provide detailed insight into understanding of how drugs affect diseases in the human body.https://doi.org/10.1038/s41598-017-07448-6
collection DOAJ
language English
format Article
sources DOAJ
author Hasun Yu
Jinmyung Jung
Seyeol Yoon
Mijin Kwon
Sunghwa Bae
Soorin Yim
Jaehyun Lee
Seunghyun Kim
Yeeok Kang
Doheon Lee
spellingShingle Hasun Yu
Jinmyung Jung
Seyeol Yoon
Mijin Kwon
Sunghwa Bae
Soorin Yim
Jaehyun Lee
Seunghyun Kim
Yeeok Kang
Doheon Lee
CODA: Integrating multi-level context-oriented directed associations for analysis of drug effects
Scientific Reports
author_facet Hasun Yu
Jinmyung Jung
Seyeol Yoon
Mijin Kwon
Sunghwa Bae
Soorin Yim
Jaehyun Lee
Seunghyun Kim
Yeeok Kang
Doheon Lee
author_sort Hasun Yu
title CODA: Integrating multi-level context-oriented directed associations for analysis of drug effects
title_short CODA: Integrating multi-level context-oriented directed associations for analysis of drug effects
title_full CODA: Integrating multi-level context-oriented directed associations for analysis of drug effects
title_fullStr CODA: Integrating multi-level context-oriented directed associations for analysis of drug effects
title_full_unstemmed CODA: Integrating multi-level context-oriented directed associations for analysis of drug effects
title_sort coda: integrating multi-level context-oriented directed associations for analysis of drug effects
publisher Nature Publishing Group
series Scientific Reports
issn 2045-2322
publishDate 2017-08-01
description Abstract In silico network-based methods have shown promising results in the field of drug development. Yet, most of networks used in the previous research have not included context information even though biological associations actually do appear in the specific contexts. Here, we reconstruct an anatomical context-specific network by assigning contexts to biological associations using protein expression data and scientific literature. Furthermore, we employ the context-specific network for the analysis of drug effects with a proximity measure between drug targets and diseases. Distinct from previous context-specific networks, intercellular associations and phenomic level entities such as biological processes are included in our network to represent the human body. It is observed that performances in inferring drug-disease associations are increased by adding context information and phenomic level entities. In particular, hypertension, a disease related to multiple organs and associated with several phenomic level entities, is analyzed in detail to investigate how our network facilitates the inference of drug-disease associations. Our results indicate that the inclusion of context information, intercellular associations, and phenomic level entities can contribute towards a better prediction of drug-disease associations and provide detailed insight into understanding of how drugs affect diseases in the human body.
url https://doi.org/10.1038/s41598-017-07448-6
work_keys_str_mv AT hasunyu codaintegratingmultilevelcontextorienteddirectedassociationsforanalysisofdrugeffects
AT jinmyungjung codaintegratingmultilevelcontextorienteddirectedassociationsforanalysisofdrugeffects
AT seyeolyoon codaintegratingmultilevelcontextorienteddirectedassociationsforanalysisofdrugeffects
AT mijinkwon codaintegratingmultilevelcontextorienteddirectedassociationsforanalysisofdrugeffects
AT sunghwabae codaintegratingmultilevelcontextorienteddirectedassociationsforanalysisofdrugeffects
AT soorinyim codaintegratingmultilevelcontextorienteddirectedassociationsforanalysisofdrugeffects
AT jaehyunlee codaintegratingmultilevelcontextorienteddirectedassociationsforanalysisofdrugeffects
AT seunghyunkim codaintegratingmultilevelcontextorienteddirectedassociationsforanalysisofdrugeffects
AT yeeokkang codaintegratingmultilevelcontextorienteddirectedassociationsforanalysisofdrugeffects
AT doheonlee codaintegratingmultilevelcontextorienteddirectedassociationsforanalysisofdrugeffects
_version_ 1724396272964599808