title: Identifying Liver Cancer and Its Relations with Diseases, Drugs, and Genes: A Literature-Based Approach.
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.
authors.affiliation: College of Computing and Informatics, Drexel University, Philadelphia, PA, United States of America.
authors.forename: Yongjun
authors.identifier: 0000-0003-4787-5122
authors.initials: Y
authors.lastname: Zhu
authors.affiliation: Department of Library and Information Science, Yonsei University, Seoul, Republic of Korea.
authors.forename: Min
authors.initials: M
authors.lastname: Song
authors.affiliation: College of Computing and Informatics, Drexel University, Philadelphia, PA, United States of America.
authors.forename: Erjia
authors.identifier: 0000-0002-0365-9340
authors.initials: E
authors.lastname: Yan
mesh_terms: D006801:Humans; D000465:Algorithms; D008113:Liver Neoplasms / Q000188:drug therapy / Q000453:epidemiology / Q000235:genetics