• HOME
  • NEWS
  • EXPLORE
    • CAREER
      • Companies
      • Jobs
    • EVENTS
    • iGEM
      • News
      • Team
    • PHOTOS
    • VIDEO
    • WIKI
  • BLOG
  • COMMUNITY
    • FACEBOOK
    • INSTAGRAM
    • TWITTER
Friday, March 27, 2026
BIOENGINEER.ORG
No Result
View All Result
  • Login
  • HOME
  • NEWS
  • EXPLORE
    • CAREER
      • Companies
      • Jobs
        • Lecturer
        • PhD Studentship
        • Postdoc
        • Research Assistant
    • EVENTS
    • iGEM
      • News
      • Team
    • PHOTOS
    • VIDEO
    • WIKI
  • BLOG
  • COMMUNITY
    • FACEBOOK
    • INSTAGRAM
    • TWITTER
  • HOME
  • NEWS
  • EXPLORE
    • CAREER
      • Companies
      • Jobs
        • Lecturer
        • PhD Studentship
        • Postdoc
        • Research Assistant
    • EVENTS
    • iGEM
      • News
      • Team
    • PHOTOS
    • VIDEO
    • WIKI
  • BLOG
  • COMMUNITY
    • FACEBOOK
    • INSTAGRAM
    • TWITTER
No Result
View All Result
Bioengineer.org
No Result
View All Result
Home NEWS Science News Health

Brussels scientists developed an AI method to improve rare disease diagnosis

Bioengineer by Bioengineer
June 5, 2019
in Health
Reading Time: 2 mins read
0
Share on FacebookShare on TwitterShare on LinkedinShare on RedditShare on Telegram

The team under Professor Tom Lenaerts (VUB-ULB) of the IB² has developed an AI algorithm that makes it possible to identify combinations of genetic variants or abnormalities that cause rare diseases through computer analysis. The algorithm was developed with Prof. dr. Guillaume Smits (Center for Human Genetics of the ULB, the Erasmus Hospital and the University Children’s Hospital Queen Fabiola) and was designed and built in collaboration with Yves Moreau and Jan Aerts (KU Leuven), Sonia Van Dooren (UZ Brussel) and Ann Nowé (Vrije Universiteit Brussel). The method has been named VarCoPP (Variant Combinations Pathogenicity Predictor).

Almost 80% of rare diseases are genetically determined. It is therefore important for doctors to be able to predict which genetic variants in the patient’s genome may be the cause of the disease. Predicting the cause of the error is not easy but predicting whether a combination of errors in different genes has the potential to cause a rare disease is even more difficult. However, this is necessary for the better diagnoses of genetic diseases since, in many cases, only a fraction of patients can be helped.

The VarCoPP algorithm offers precisely that innovative approach: it makes it possible to simultaneously test the combinations of different variants in gene pairs and to predict their potential pathogenicity. The AI that underlies VarCoPP is driven by the database of rare diseases called DIDA (dida.ibsquare.be), which was developed by the same researchers in 2015. The researchers successfully tested the effectiveness and reliability of the algorithm on 23 independent pathogenic gene combinations, and deliver confidence intervals of 95% and 99% to help doctors zoom in on the most important predictions. The team is now attempting to use these results to identify the genetic causes of rare diseases in patients for whom no cause could previously be identified. The team introduces at the same time a new online diagnostic platform for researchers and clinicians, based on the algorithm. The platform is called ‘ORVAL’ and is described in a publication in the journal Nucleic Acids Research (NAR).

ORVAL and VarCoPP provide a novel approach to study variant combinations for rare diseases for which causal genes are known or unknown, such as for example the hundreds of autism or epilepsy genes or the 20 genes of the rare Bardet-Biedl syndrome (a genetic disorder which presents blindness, obesity and motor disorders amongst others) where different combinations of genetic variations are likely to be the cause.

###

Media Contact
Tom Lenaerts
[email protected]
http://dx.doi.org/10.1073/pnas.1815601116

Tags: Medicine/HealthRobotry/Artificial Intelligence
Share12Tweet8Share2ShareShareShare2

Related Posts

Aversive Learning Hijacks Brain Sugar Sensor

March 25, 2026

Can Psychosocial Factors Influence Cancer Risk?

March 23, 2026

Depression Factors in Elderly: Pre vs. Post-COVID Analysis

March 23, 2026

Hidden Health Crises Among US and UK Volunteers in Ukraine Uncovered in New Study

March 23, 2026
Please login to join discussion

POPULAR NEWS

  • blank

    Revolutionary AI Model Enhances Precision in Detecting Food Contamination

    96 shares
    Share 38 Tweet 24
  • Imagine a Social Media Feed That Challenges Your Views Instead of Reinforcing Them

    1003 shares
    Share 397 Tweet 248
  • Uncovering Functions of Cavernous Malformation Proteins in Organoids

    54 shares
    Share 22 Tweet 14
  • Promising Outcomes from First Clinical Trials of Gene Regulation in Epilepsy

    51 shares
    Share 20 Tweet 13

About

We bring you the latest biotechnology news from best research centers and universities around the world. Check our website.

Follow us

Recent News

In-Sensor Cryptography Links Physical Process to Digital Identity

Can Psychosocial Factors Influence Cancer Risk?

Depression Factors in Elderly: Pre vs. Post-COVID Analysis

Subscribe to Blog via Email

Success! An email was just sent to confirm your subscription. Please find the email now and click 'Confirm' to start subscribing.

Join 78 other subscribers
  • Contact Us

Bioengineer.org © Copyright 2023 All Rights Reserved.

Welcome Back!

Login to your account below

Forgotten Password?

Retrieve your password

Please enter your username or email address to reset your password.

Log In
No Result
View All Result
  • Homepages
    • Home Page 1
    • Home Page 2
  • News
  • National
  • Business
  • Health
  • Lifestyle
  • Science

Bioengineer.org © Copyright 2023 All Rights Reserved.