DiseaseConnect: a comprehensive web server for mechanism-based disease-disease connections

• Published in: Nucleic acids research Vol. 42; no. Web Server issue; pp. W137 - W146
• Main Authors: Liu, Chun-Chi, Tseng, Yu-Ting, Li, Wenyuan, Wu, Chia-Yu, Mayzus, Ilya, Rzhetsky, Andrey, Sun, Fengzhu, Waterman, Michael, Chen, Jeremy J W, Chaudhary, Preet M, Loscalzo, Joseph, Crandall, Edward, Zhou, Xianghong Jasmine
• Format: Journal Article
• Language: English
• Published: England Oxford University Press 01-07-2014
• Subjects: Comorbidity; Disease - genetics; Drug Therapy; Gene Expression; Humans; Internet; MicroRNAs - metabolism; Polymorphism, Single Nucleotide; Software
• ISSN: 0305-1048; 1362-4962
• DOI: 10.1093/nar/gku412

The DiseaseConnect (http://disease-connect.org) is a web server for analysis and visualization of a comprehensive knowledge on mechanism-based disease connectivity. The traditional disease classification system groups diseases with similar clinical symptoms and phenotypic traits. Thus, diseases with entirely different pathologies could be grouped together, leading to a similar treatment design. Such problems could be avoided if diseases were classified based on their molecular mechanisms. Connecting diseases with similar pathological mechanisms could inspire novel strategies on the effective repositioning of existing drugs and therapies. Although there have been several studies attempting to generate disease connectivity networks, they have not yet utilized the enormous and rapidly growing public repositories of disease-related omics data and literature, two primary resources capable of providing insights into disease connections at an unprecedented level of detail. Our DiseaseConnect, the first public web server, integrates comprehensive omics and literature data, including a large amount of gene expression data, Genome-Wide Association Studies catalog, and text-mined knowledge, to discover disease-disease connectivity via common molecular mechanisms. Moreover, the clinical comorbidity data and a comprehensive compilation of known drug-disease relationships are additionally utilized for advancing the understanding of the disease landscape and for facilitating the mechanism-based development of new drug treatments.