Computational Methods for Identifying Similar Diseases

Although our knowledge of human diseases has increased dramatically, the molecular basis, phenotypic traits, and therapeutic targets of most diseases still remain unclear. An increasing number of studies have observed that similar diseases often are caused by similar molecules, can be diagnosed by s...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Molecular therapy. Nucleic acids Jg. 18; S. 590 - 604
Hauptverfasser: Cheng, Liang, Zhao, Hengqiang, Wang, Pingping, Zhou, Wenyang, Luo, Meng, Li, Tianxin, Han, Junwei, Liu, Shulin, Jiang, Qinghua
Format: Journal Article
Sprache:Englisch
Veröffentlicht: United States Elsevier Inc 06.12.2019
Elsevier Limited
American Society of Gene & Cell Therapy
Elsevier
Schlagworte:
Annotations
Computer applications
Disease
disease similarity
Drug development
Drug dosages
Genes
MicroRNAs
molecular basis
Names
ncRNA function
Non-coding RNA
Ontology
Phenotypes
phenotypic traits
Ribonucleic acid
RNA
Therapeutic applications
therapeutic drugs
disease similarity
ncRNA function
therapeutic drugs
phenotypic traits
molecular basis
ISSN:2162-2531, 2162-2531
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:Although our knowledge of human diseases has increased dramatically, the molecular basis, phenotypic traits, and therapeutic targets of most diseases still remain unclear. An increasing number of studies have observed that similar diseases often are caused by similar molecules, can be diagnosed by similar markers or phenotypes, or can be cured by similar drugs. Thus, the identification of diseases similar to known ones has attracted considerable attention worldwide. To this end, the associations between diseases at the molecular, phenotypic, and taxonomic levels were used to measure the pairwise similarity in diseases. The corresponding performance assessment strategies for these methods involving the terms “category-based,” “simulated-patient-based,” and “benchmark-data-based” were thus further emphasized. Then, frequently used methods were evaluated using a benchmark-data-based strategy. To facilitate the assessment of disease similarity scores, researchers have designed dozens of tools that implement these methods for calculating disease similarity. Currently, disease similarity has been advantageous in predicting noncoding RNA (ncRNA) function and therapeutic drugs for diseases. In this article, we review disease similarity methods, evaluation strategies, tools, and their applications in the biomedical community. We further evaluate the performance of these methods and discuss the current limitations and future trends for calculating disease similarity.
Bibliographie:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ObjectType-Review-3
content type line 23
ISSN:2162-2531
2162-2531
DOI:10.1016/j.omtn.2019.09.019