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 | |
| Publication status | Published - 2016 May 1 |
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All Science Journal Classification (ASJC) codes
- Biochemistry, Genetics and Molecular Biology(all)
- Agricultural and Biological Sciences(all)
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Identifying liver cancer and its relations with diseases, drugs, and genes : A literature-based approach. / Zhu, Yongjun; Song, Min; Yan, Erjia.
In: PloS one, Vol. 11, No. 5, e0156091, 01.05.2016.Research output: Contribution to journal › Article
TY - JOUR
T1 - Identifying liver cancer and its relations with diseases, drugs, and genes
T2 - A literature-based approach
AU - Zhu, Yongjun
AU - Song, Min
AU - Yan, Erjia
PY - 2016/5/1
Y1 - 2016/5/1
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=84971224860&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84971224860&partnerID=8YFLogxK
U2 - 10.1371/journal.pone.0156091
DO - 10.1371/journal.pone.0156091
M3 - Article
C2 - 27195695
AN - SCOPUS:84971224860
VL - 11
JO - PLoS One
JF - PLoS One
SN - 1932-6203
IS - 5
M1 - e0156091
ER -