Identifying liver cancer and its relations with diseases, drugs, and genes: A literature-based approach

Yongjun Zhu; Min Song; Erjia Yan

doi:10.1371/journal.pone.0156091

Identifying liver cancer and its relations with diseases, drugs, and genes: A literature-based approach

Yongjun Zhu, Min Song, Erjia Yan

Department of Library and Information Science

Research output: Contribution to journal › Article › peer-review

9 Citations (Scopus)

Abstract

In biomedicine, scientific literature is a valuable source for knowledge discovery. Mining knowledge from textual data has become an ever important task as the volume of scientific literature is growing unprecedentedly. In this paper, we propose a framework for examining a certain disease based on existing information provided by scientific literature. Disease-related entities that include diseases, drugs, and genes are systematically extracted and analyzed using a three-level network-based approach. A paper-entity network and an entity co-occurrence network (macro-level) are explored and used to construct six entity specific networks (meso-level). Important diseases, drugs, and genes as well as salient entity relations (micro-level) are identified from these networks. Results obtained from the literature-based literature mining can serve to assist clinical applications.

Original language	English
Article number	e0156091
Journal	PloS one
Volume	11
Issue number	5
DOIs	https://doi.org/10.1371/journal.pone.0156091
Publication status	Published - 2016 May 1

Bibliographical note

Funding Information:
This project was made possible in part by the Institute of Museum and Library Services (Grant Award Number: RE-07-15-0060-15), for the project titled "Building an entity-based research framework to enhance digital services on knowledge discovery and delivery". In addition, the project was supported partly by the Bio-Synergy Research Project (NRF-2013M3A9C4078138) of the Ministry of Science, ICT and Future Planning through the National Research Foundation.

Publisher Copyright:
© 2016 Zhu et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

All Science Journal Classification (ASJC) codes

Biochemistry, Genetics and Molecular Biology(all)
Agricultural and Biological Sciences(all)
General

UN SDGs

This output contributes to the following Sustainable Development Goal(s)

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abstract = "In biomedicine, scientific literature is a valuable source for knowledge discovery. Mining knowledge from textual data has become an ever important task as the volume of scientific literature is growing unprecedentedly. In this paper, we propose a framework for examining a certain disease based on existing information provided by scientific literature. Disease-related entities that include diseases, drugs, and genes are systematically extracted and analyzed using a three-level network-based approach. A paper-entity network and an entity co-occurrence network (macro-level) are explored and used to construct six entity specific networks (meso-level). Important diseases, drugs, and genes as well as salient entity relations (micro-level) are identified from these networks. Results obtained from the literature-based literature mining can serve to assist clinical applications.",

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Identifying liver cancer and its relations with diseases, drugs, and genes: A literature-based approach

Abstract

Bibliographical note

All Science Journal Classification (ASJC) codes

UN SDGs

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