The DOI matches its Crossref record; 18 of the 18 references it cites were found in a registry or an index.
The DisGeNET cytoscape app: Exploring and visualizing disease genomics data
Open accessAbstract
Thanks to the unbiased exploration of genomic variants at large scale, hundreds of thousands of disease-associated loci have been uncovered. In parallel, network-based approaches have proven to be essential to understand the molecular mechanisms underlying human diseases. The use of these approaches has been boosted by the abundance of information about disease associated genes and variants, high quality human interactomics data, and the emergence of new types of omics data. The DisGeNET Cytoscape App combines the capabilities of Cytoscape with those of DisGeNET, a knowledge platform based on a comprehensive catalogue of disease-associated genes and variants. The DisGeNET Cytoscape App contains functions to query, analyze, and visualize different network representations of the gene-disease and variant-disease associations available in DisGeNET. It supports a wide variety of applications through its query and filter functionalities, including the annotation of foreign networks generated by other apps or uploaded by the user. The new release of the DisGeNET Cytoscape App has been designed to support Cytoscape 3.x and incorporates novel distinctive features such as visualization and analysis of variant-disease networks, disease enrichment analysis for genes and variants, and analytic support through Cytoscape Automation. Moreover, the DisGeNET Cytoscape App features an API to access its core functionalities via the REST protocol fostering the development of reproducible and scalable analysis workflows based on DisGeNET data.
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Cites
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Cited by
Littman, R., Cheng, M., Wang, N., Peng, C., & Yang, X. (2023) · iScience · doi:10.1016/j.isci.2023.107124 · Cited by 35
Hossain, M. M., Adhikari, J., Dutta, A., Khandaker, A., Islam, S., Rahman, M. M., & Shibly, A. Z. (2025) · PLOS One · doi:10.1371/journal.pone.0331339 · Cited by 11
Sebastian, S., Roy, S., & Kalita, J. (2025) · Journal of Biomedical Informatics · doi:10.1016/j.jbi.2025.104797 · Cited by 10
Uzuner Odongo, D., İlgün, A., Bozkurt, F. B., & Çakır, T. (2025) · Communications Biology · doi:10.1038/s42003-025-07941-z · Cited by 4
Metadata
- Authors
- Piñero, J., Saüch, J., Sanz, F., & Furlong, L. I.
- Venue
- Computational and Structural Biotechnology Journal
- Published
- 2021
- Volume
- 19
- Pages
- 2960-2967
- ISSN
- 2001-0370 (ISSN-L)
- OpenAlex
- W3162538759
- Cited by
- 544
- References
- 18
- FWCI
- 26.43
- Type
- journal article
- Language
- en
- Open access
- gold
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