Science Spotlight: Cancer prognosis via deep learning, new protein degraders, and more

A pair of publications in Science and Nature highlight continued progress in deep learning methods for cancer diagnosis and prognosis, in one case by linking non-coding mutations to changes in gene regulation and in the other by further improving histopathology assessment.

In the first study, published in Science, a group at Stanford, in collaboration with Illumina Inc. (NASDAQ:ILMN), Nvidia Corp. (NASDAQ:NVDA) and The Cancer Genome Atlas Analysis Network, aim to identify changes in the regulatory networks that control chromatin accessibility, and thereby gene expression, in cancer cells with non-coding mutations. ...