Main challenges in disease genomics

disease genomics

DISGENET plus

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Most human diseases are influenced by our genes. Identifying the genes that cause diseases is key to pinpoint novel strategies for prevention and treatment.

  • Brings the power of AI and genetics together

  • Makes the access to disease genomics data easy

Based on the community-recognized DisGeNET platform, a resource widely used in the biomedical community with over 70,000 users per year, cited by more than 2,500 publications and one the ELIXIR Recommended Interoperability Resources.

DISGENET plus key features:

  • State-of-the-art text mining technology (deep learning and language models)
  • Increased coverage of animal models
  • Metrics and scores to prioritize the information
  • Most recent findings from the literature readily available
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Text mining performance of 92% (F-score)

Check our use cases

Selected Publications

Our foundation comes from the first step of innovation, research.

J. Piñero, J. M. Ramírez-Anguita, J. Saüch-Pitarch, F. Ronzano, E. Centeno, F. Sanz, and L. I. Furlong. The DisGeNET knowledge platform for disease genomics: 2019 update. Nucleic Acids Research, 48(D1):D845–D855, 2020. doi:10.1093/nar/gkz1021.

J. Piñero, A. Bravo, N. Queralt-Rosinach, A. Gutiérrez-Sacristán, J. Deu-Pons, E. Cen- teno, J. García-García, F. Sanz, L. I. Furlong, À. Bravo, N. Queralt-Rosinach, A. Gutiérrez-Sacristán, J. Deu-Pons, E. Centeno, J. García-García, F. Sanz, and L. I. Furlong. DisGeNET: a comprehensive platform integrating information on human disease-associated genes and variants. Nucleic Acids Research, 45(D1):D833–D839, 2017. doi:10.1093/nar/gkw943.

N. Queralt-Rosinach, J. Piñero, À. Bravo, F. Sanz, and L. I. Furlong. DisGeNET-RDF: harnessing the innovative power of the Semantic Web to explore the genetic basis of diseases. Bioinformatics, 32(14):2236–2238, 2016. doi:10.1093/bioinformatics/btw214.

N. Queralt-Rosinach, T. Kuhn, C. Chichester, M. Dumontier, F. Sanz, and L. I. Fur- long. Publishing DisGeNET as nanopublications. Semantic Web, 7(5):519–528, 2016. doi:10.3233/SW-150189.

J. Piñero, N. Queralt-Rosinach, À. Bravo, J. Deu-Pons, A. Bauer-Mehren, M. Baron, F. Sanz, and L. I. Furlong. DisGeNET: a discovery platform for the dynamical exploration of human diseases and their genes. Database, 2015, 2015. doi:10.1093/database/bav028.

A. Bauer-Mehren, M. Bundschus, M. Rautschka, M. A. Mayer, F. Sanz, and L. I. Furlong. Gene-disease network analysis reveals functional modules in mendelian, complex and environmental diseases. PloS One, 6(6):e20284, 2011. doi:10.1371/journal.pone.0020284.

A. Bauer-Mehren, M. Rautschka, F. Sanz, and L. I. Furlong. DisGeNET: a Cytoscape plugin to visualize, integrate, search and analyze gene–disease networks. Bioinformatics, 26(22):2924–2926, 2010. doi:10.1093/bioinformatics/btq538.

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