Ignet: A centrality and INO-based web system for analyzing and visualizing literature-mined networks

Arzucan Özgür; Junguk Hur; Zuoshuang Xiang; Edison Ong; Dragomir R. Radev; Yongqun He

Ignet: A centrality and INO-based web system for analyzing and visualizing literature-mined networks

Arzucan Özgür, Junguk Hur, Zuoshuang Xiang, Edison Ong, Dragomir R. Radev, Yongqun He

Research output: Contribution to journal › Conference article › peer-review

Abstract

Ignet (Integrative Gene Network) is a web-based system for dynamically updating and analyzing gene interaction networks mined using all PubMed abstracts. Four centrality metrics, namely degree, eigenvector, betweenness, and closeness are used to determine the importance of genes in the networks. Different gene interaction types between genes are classified using the Interaction Network Ontology (INO) that classifies interaction types in an ontological hierarchy along with individual keywords listed for each interaction type. An interactive user interface is designed to explore the interaction network as well as the centrality and ontology based network analysis. Availability: http://ignet.hegroup.org.

Original language	English (US)
Journal	CEUR Workshop Proceedings
Volume	1747
State	Published - 2016
Externally published	Yes
Event	2016 Joint International Conference on Biological Ontology and BioCreative - Food, Nutrition, Health and Environment for the 9 Billion, ICBO-BioCreative 2016 - Corvallis, United States Duration: Aug 1 2016 → Aug 4 2016

ASJC Scopus subject areas

Computer Science(all)

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title = "Ignet: A centrality and INO-based web system for analyzing and visualizing literature-mined networks",

abstract = "Ignet (Integrative Gene Network) is a web-based system for dynamically updating and analyzing gene interaction networks mined using all PubMed abstracts. Four centrality metrics, namely degree, eigenvector, betweenness, and closeness are used to determine the importance of genes in the networks. Different gene interaction types between genes are classified using the Interaction Network Ontology (INO) that classifies interaction types in an ontological hierarchy along with individual keywords listed for each interaction type. An interactive user interface is designed to explore the interaction network as well as the centrality and ontology based network analysis. Availability: http://ignet.hegroup.org.",

author = "Arzucan {\"O}zg{\"u}r and Junguk Hur and Zuoshuang Xiang and Edison Ong and Radev, {Dragomir R.} and Yongqun He",

year = "2016",

language = "English (US)",

volume = "1747",

journal = "CEUR Workshop Proceedings",

issn = "1613-0073",

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note = "2016 Joint International Conference on Biological Ontology and BioCreative - Food, Nutrition, Health and Environment for the 9 Billion, ICBO-BioCreative 2016 ; Conference date: 01-08-2016 Through 04-08-2016",

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T2 - 2016 Joint International Conference on Biological Ontology and BioCreative - Food, Nutrition, Health and Environment for the 9 Billion, ICBO-BioCreative 2016

AU - Özgür, Arzucan

AU - Hur, Junguk

AU - Xiang, Zuoshuang

AU - Ong, Edison

AU - Radev, Dragomir R.

AU - He, Yongqun

PY - 2016

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AB - Ignet (Integrative Gene Network) is a web-based system for dynamically updating and analyzing gene interaction networks mined using all PubMed abstracts. Four centrality metrics, namely degree, eigenvector, betweenness, and closeness are used to determine the importance of genes in the networks. Different gene interaction types between genes are classified using the Interaction Network Ontology (INO) that classifies interaction types in an ontological hierarchy along with individual keywords listed for each interaction type. An interactive user interface is designed to explore the interaction network as well as the centrality and ontology based network analysis. Availability: http://ignet.hegroup.org.

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