SAVANA uses a machine learning algorithm to identify cancer-specific structural variations and copy number aberrations in long-read DNA sequencing data. The complex structure of cancer genomes means ...

In a way, sequencing DNA is very simple: There's a molecule, you look at it, and you write down what you find. You'd think it would be easy—and, for any one letter in the sequence, it is. The problem ...

A breakthrough by researchers at Peter Mac will allow scientists to detect, analyze and profile cancer tumors in patients via a simple blood test. The Dawson lab at Peter Mac has developed a method ...

Our genetic heritage is not a blueprint or an algorithm, as many biologists have imagined, but something else entirely.

A group of a few dozen colorful translucent 3D blobs, many of which overlap, contain brightly colored dots against a black background. Three-dimensional transcriptomics data from an instrument ...

Blood tests have proved to be a promising tool for detecting and monitoring cancer. Researchers at Chalmers University of Technology and the University of Gothenburg, Sweden, have now developed a new ...

Scientists have developed a new way to improve the reliability of DNA origami for future biomedical, agritech and other ...

Researchers at EMBL’s European Bioinformatics Institute (EMBL-EBI) have developed a new machine learning method called SAVANA that significantly reduces sequencing errors for cancer genomes. Long-read ...