News

Keep up with the latest news from the NCI Center for Biomedical Informatics and Information Technology (CBIIT) and the data science communities.

A new spatial transcriptomics tool, called Spotiphy, can help you visualize gene distribution patterns across entire tissue sections, giving you a more complete picture of the tumor and its microenvironment.

See how a new AI-driven tool can help you measure micronuclei and similar structures to study their underlying biology, enabling you to more efficiently measure and characterize these tiny structures.

Thanks to this NCI-funded study, you now have a host of top-performing predictive models, data types, and training algorithms to help you better classify your patient samples.

Do you work with fusion oncoproteins? Explore a new protein language model (pLM) that NCI-funded researchers trained on fusion oncoproteins to advance discoveries in fusion-driven cancers!

Learn how CGS-Net can assist in diagnosing cancer by incorporating contextual information for more accurate segmentation in medical images.

Discover the outputs of different-sized gene and protein networks (“interactomes”) and use an NCI-funded evaluation pipeline tool for assessing and integrating the best interactomes for your work.

A new computational model reveals how local tumor conditions impact therapy effectiveness.

Here at NCI, how are we maximizing data utility? Two of our leaders comment on the ways we’re making data ready for use with artificial intelligence (AI), more valuable to the cancer research community, and more!

The NCI Cancer Research Data Commons (CRDC) is a great resource for accessing cancer research data. So, how have your colleagues been using it recently? Read this article to find out!

What influences the performance of an AI model more: where the researcher collected the data, or how? NCI-funded researchers set out to investigate some of the factors that could influence the performance of an AI-based image model screening for cervical cancer.