Resources >‏ News >‏ News Details

News Details

QCRI scientists develop algorithm to detect brain cancer markers

Publication Date:
30/01/2018
Category:
News
bioinformatics cancer pic.jpg
Scientists from the Qatar Computing Research Institute have developed a new algorithm that can identify driver genes of several types of gliomas, the most common and aggressive forms of primary brain tumors.

The QCRI researchers, including Dr. Raghvendra Mall, Dr. Halima Bensmail and Khalid Kunji, built a machine-learning algorithm that can identify the main regulators of separate brain tumors.

Knowledge of the purpose of these driver genes and the status of these cancer subtypes could further assist in the search for treatments or prognostic information in both glioma and other cancer types. The work reveals the identity and biological activities of the main genes that regulate and characterize the differences between different glioma subtypes.

The method was recently published in the journals Nucleic Acids Research and Nature.

It was a collaboration with scientists from Italy’s University of Sannio - including former QCRI acting research director Dr. Michele Ceccarelli - along with researchers from Columbia University Medical Center and Henry Ford Health Systems.

“The algorithm outperforms state-of-the-art methods for genome-wide gene regulatory network inference by incorporating prior biological knowledge and regularization to prune false positives,” said Dr. Mall.

The technique can also be used for other problems in medicine beyond brain tumors. It is applicable to other cancers including breast, ovarian and lung cancer to identify key driver genes, and can also potentially be used to identify key therapeutic targets in diseases prevalent in Qatar, such as diabetes and obesity.

This recent work builds on previous QCRI research published in the journal Cell in 2016 that developed algorithms which identified the different subtypes of glioma based on their aggressiveness.

Gliomas represent about 15 percent of all brain tumors, affecting about three people in 100,000 annually. The most common duration of survival following diagnosis is 12 to 15 months, with fewer than 3 to 5 percent of people surviving longer than five years.


Follow Us

  • YouTube
  • Twitter
  • Facebook
  • RSS Feed
  • Linkedin
  • github-web.png
Back to Top

In the Media

Forbes fake news pic.jpg

Can AI Put An End To Fake News? Don't Be So Sure

07/10/2018

Fake news was the Collin’s word of the year for 2017 with good reason. In a year where politics-as-usual was torn apart at the seams, high-profile scandals rocked our faith in humanity and the ...

Read More

roadtracer.png

MIT/QCRI system uses machine learning to build road maps

22/04/2018

Map apps may have changed our world, but they still haven’t mapped all of it yet. Specifically, mapping roads can be difficult and tedious: even after taking aerial images, companies still have to ...

Read More

Economist story pic.JPG

Improving disaster response efforts through data

08/02/2018

Extreme weather events put the most vulnerable communities at high risk. How can data analytics strengthen early warning systems and and support relief efforts for communities in need? The size and ...

Read More

Events

Past Events

2018

Eman interns pic 2017.jpg

QCRI Summer Internship Program

Download ICS File 06/05/2018  - 05/07/2018 , Hamad Bin Khalifa Research Complex

Each year, Qatar Computing Research Institute organizes a summer internship program for undergraduate students studying computer science, computer engineering and other disciplines. The internship is unpaid, and QCRI does not provide any visa support.

Read More

Regina

Public Talk by Prof. Regina Barzilay "Artificial Intelligence for Oncology: Learning to Cure Cancer from Images and Text"

Download ICS File 27/03/2018 ,

Artificial Intelligence for Oncology: Learning to Cure Cancer from Images and Text A talk by Professor Regina Barzilay, MIT CSAIL Winner of 2017 MacArthur ‘genius grant’ At Education City Student ...

Read More

Slide1.JPG

QCRI & MIT-CSAIL Annual Project Review 2018

Download ICS File 27/03/2018 ,

Executive Overview Sessions Open to public Date:    Tuesday, March 27, 2018 Time:    9:00AM – 3:00PM Venue:  HBKU Research Complex Multipurpose Room To view full agenda, please click here . To RSVP, ...

Read More

News

Darb Al Saai QCRI 2017.JPG

QCRI to offer kids’ computing activities at this year’s Darb Al Saai

03/12/2018

Tech fun and robotics computing activities will be available to children attending the annual family celebration from December 12 to 20.

Read More

Sofiane Abbar in his office.jpg

Global experts in artificial intelligence for transportation to visit Qatar for TASMU-QCAI workshop

18/11/2018

Urban computing experts from Europe, the US and Qatar are to discuss state-of-the-art advances in artificial intelligence for transportation with local stakeholders.

Read More

Francisco Martin - Source_TelefonicaOpenFuture_.jpg

QCAI to Conduct Joint Machine Learning School with BigML

16/10/2018

Two-day crash course to provide hands-on introduction to machine learning for industry practitioners, developers, graduate students and undergraduates.

Read More