Data for tomorrow

Streamlining the journey from complex data to actionable insights

Speed up safe and sustainable product development by leveraging the power of AI, knowledge graphs and NLP

Gain access to the most recent and relevant data on disease genomics to accelerate drug R&D and unlock new precision medicine possibilities.

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Natural Language Processing

Our state-of the-art NLP solutions make your textual data searchable, analyzable and actionable. We help you speed up informed innovation with data unlocked from text.

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AI & Knowledge Graphs

We enable you to reveal insights from complex biological networks providing fine-grained, comprehensive coverage of intricate relationships between biomolecules.

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DISGENET, the world’s most reliable & extensive gene-disease database

Get immediate access to information comparable to having read over 30 million articles.

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45M+

disease associations

+5,500

citations worldwide

92%

NLP F-score

Est.

2010

MedBioinformatics, expanding DISGENET’s potential

MedBioinformatics is built on over 15 years of life science expertise. We unlock the true potential of your data through cutting-edge methods in data analytics, semantic integration, and NLP. This empowers you to develop innovative and safer products, prioritizing human health and well-being.

Explore our story

What do customers and researchers say about us?

“When exploring the DNA methylation of Cri du Chat patients, DISGENET helped me find interesting connections between genes with DNA methylation changes in the promoter and disease phenotypes. This analysis was suggestive of the DNA methylation itself having a role in developing the characteristics of this understudied rare disease.”

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Petter Holland, PhD

Researcher at Oslo University Hospital, Norway
“We use DISGENET to search for variants that cause rare diseases. The most difficult part of variant searching is finding appropriate references and presenting evidence, and DISGENET’s large and well-structured database makes it easy to find.”

June-Young Koh

Chief Research Officer & Head of RARE TFT, Inocras
“DISGENET has been a game-changer in our research endeavors. Our project revolves around understanding the consequences of protein misfolding, a phenomenon where proteins fail to adopt their native, functional structure, thereby impacting biological processes and contributing to disease pathology. We wholeheartedly recommend DISGENET to other researchers and colleagues working in similar domains.”

Maria F. Anglero

Research Assistant, Pennsylvania State University

Read the latest articles on our blog

Anticipating Drug Toxicity: data-driven drug safety with DISGENET

Article September 12, 2023

Key points Flupirtine, an aminopyridine introduced in 1984 as a non-opioid analgesic for acute and chronic pain, embarked on a tumultuous journey within the medical landscape. Initially approved for broad pain management, its trajectory shifted in 2013 due to concerns over liver toxicity. The European Medicines Agency (EMA) limited its use to acute pain for […]
Genetics for drug and chemical risk assessment

Article March 9, 2023

In recent years, there has been an increasing appreciation of the need to consider variability in human populations in evaluating health risks for new and existing chemicals. Recent policies such as The Frank R. Lautenberg Chemical Safety for the twenty-first Century Act (2016) require the US Environmental Protection Agency to evaluate new and existing toxic chemicals with explicit […]
Genetic support for FDA approvals in 2021

Article October 6, 2022

Key points Human genetics and FDA drug approvals in 2021 There is compelling evidence of the value of incorporating genetic information in the drug development process. A drug target supported by genetic evidence has a 2-fold higher probability of successful clinical development compared to those targets with no genetic support [1]. A systematic analysis of FDA […]
Meet our team: Jordi Valls

Interview May 6, 2022

Jordi Valls is a Postdoctoral Researcher and experienced bioinformatics in the field of genomic analysis. At MedBioInformatics, Dr Valls is currently working on RISKHUNT3R, a European H2020 Project. He is involved in characterising/identifying the adverse effects of chemical compounds on cohorts/target segments depending on their genetic information and variability, through the use of different network […]