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DALIAN UNIVERSITY OF TECHNOLOGY Login 中文
孙长凯

Professor
Supervisor of Doctorate Candidates
Supervisor of Master's Candidates


Gender:Male
Alma Mater:第四军医大学
Degree:Doctoral Degree
School/Department:人工智能学院
Discipline:Biomedical Engineering
Business Address:大连理工大学创新园大厦B1202
Contact Information:sunck2@dlut.edu.cn
E-Mail:sunck2@dlut.edu.cn
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Current position: Home >> Scientific Research >> Paper Publications

A Systems Approach to Refine Disease Taxonomy by Integrating Phenotypic and Molecular Networks

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Indexed by:期刊论文

Date of Publication:2018-05-01

Journal:EBIOMEDICINE

Included Journals:PubMed、SCIE

Volume:31

Page Number:79-91

ISSN No.:2352-3964

Key Words:Disease taxonomy; Network medicine; Disease phenotypes; Molecular profiles; Precision medicine

Abstract:The International Classification of Diseases (LCD) relies on clinical features and lags behind the current understanding of the molecular specificity of disease pathobiology, necessitating approaches that incorporate growing biomedical data for classifying diseases to meet the needs of precision medicine. Our analysis revealed that the heterogeneous molecular diversity of disease chapters and the blurred boundary between disease categories in 1CD should be further investigated. Here, we propose a new classification of diseases (NCD) by developing an algorithm that predicts the additional categories of a disease by integrating multiple networks consisting of disease phenotypes and their molecular profiles. With statistical validations from phenotype-genotype associations and interaciome networks, we demonstrate that NCD improves disease specificity owing to its overlapping categories and polyhierarchical structure. Furthermore, NCD captures the molecular diversity of diseases and defines clearer boundaries in terms of both phenotypic similarity and molecular associations, establishing a rational strategy to reform disease taxonomy. (C) 2018 The Authors. Published by Elsevier B.V.