News

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

Read this recently released collection of 13 studies to learn more about NCI’s Human Tumor Atlas Network (HTAN). You’ll gain insights into tumor development, progression, and treatment responses through advanced research methodologies and 3D tumor atlases.

This discovery could impact our understanding of the progression of pancreatic cancer and guide future research and treatment strategies.

Want to learn more about the noncoding regions of DNA that impact cancer and its resistance to treatment? A new NCI-funded computational tool called “MethNet” may help.

Looking for a new tool to help you better understand the genes that drive cancer? See how this NCI-funded tool called “HAPI” can help you spot structural changes linked to hijacked enhancers—bits of DNA that move from one location to another to boost overexpression of cancer-causing genes.

Discover how you can use it to access and visualize genomic data, making it easier for you to analyze and interpret complex omics data.

Telomeres have confounded researchers for decades, making it difficult to understand their full impact on diseases like cancer. See how this new digital telomere measurement tool is helping researchers gain insight into these elusive structures.

Looking for an easier way to sort and quantify key cellular information from immunofluorescent images? NCI-funded researchers have a new semi-automated tool, called “GammaGateR,” that may help.

An NCI-funded technology blends specific molecular markers along with traditional morphological features in the same cells and in one digital slide. This tool could someday help pathologists and ML models better predict cancer treatment response and outcomes.

An international team of researchers combined genomics, biopsy results, and artificial intelligence (AI) to track prostate cancer over time. Learn more about these “evolvability” metrics and how they could someday help predict cancer re-occurrence.

NCI-funded researchers are blending mathematics with machine learning to refine cancer treatment. In the future, this kind of virtual tumor model could help to further personalize care for people with cancer.