A computer algorithm can efficiently find genetic mutations that work together to drive cancer as well as other important genetic clues that researchers might someday use to develop new treatments for ...

Proteogenomics explores how genetic information translates into protein expression and function, and the role of changes across DNA, RNA, and proteins in influencing disease development and ...

In a groundbreaking study published on January 18, 2024, in Cancer Discovery, scientists at University of California San Diego School of Medicine leveraged a machine learning algorithm to tackle one ...

Scientists at UCLA and the University of Toronto have developed an advanced computational tool, called moPepGen, that helps identify previously invisible genetic mutations in proteins, unlocking new ...

A whole-genome sequencing approach shows early promise over current commercial methods for identifying more patients likely ...

Genetic testing, often via a blood sample, can confirm a muscular dystrophy diagnosis. It can also identify specific gene mutations to help guide treatment and determine whether or not someone is a ...