| 1 min read
Register for free to listen to this article
Listen with Speechify
0:00
1:00
STANFORD, Calif.—Stanford University researchers are looking to track down gene fusions that can drive cancers proliferation and uncover fusions in individual tumor cells. To do that, they have turned to a single-cell statistical modeling method, and a member of the team presented their method during the Bioinformatics and Artificial Intelligence minisymposium at the AACR Virtual Annual Meeting II in June.
 
In the session, Dr. Roozbeh Dehghannasin, a postdoctoral researcher at the Stanford School of Medicine, described the statistical model designed to detect gene fusions at a single-cell level, explaining that many gene fusions are known to drive cancer development, but limitations in current technologies have hindered fully understanding their functions.
 
The model developed by the Stanford team, which is called SICILIAN, can be integrated into conventional splice alignment tools to detect different RNA variants, such as splice junctions, gene fusions and circular RNA.
 
Dehghannasin said that the team found that SICILIAN detected gene fusions with similar sensitivity but greater specificity than an existing gene fusion detection tool called STAR-Fusion.

Related Topics

Published In

Volume 16 - Issue 8 | September 2020

September 2020

September 2020 Issue

Loading Next Article...
Loading Next Article...
Subscribe to Newsletter

Subscribe to our eNewsletters

Stay connected with all of the latest from Drug Discovery News.

Subscribe

Sponsored

Laboratorian with a white coat and blue gloves pipettes green liquid into a beaker with multicolored liquids in beakers and tubes in the blue-tinged, sterile laboratory background.

Discovering cutting-edge nitrosamine analysis in pharmaceuticals

New tools help researchers detect and manage harmful nitrosamine impurities in drugs such as monoclonal antibodies.
A starry night sky reflected over calm water, symbolizing the discovery of hidden patterns in complex systems.

Technology Guide: Spatial biology techniques

Discover essential strategies and expert insights to navigate the expanding world of spatial biology.
Red tumor cells are shown against a teal backdrop showing attachment to tissue.

Decoding the tumor microenvironment with immune profiling

Integrating multiplexed immunohistochemistry with spatial analysis offers a practical way to uncover tumor-immune dynamics.
Drug Discovery News March 2025 Issue
Latest IssueVolume 21 • Issue 1 • March 2025

March 2025

March 2025 Issue

Explore this issue