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

3D rendering illustation of the inside of a male body highlighting the pancreas and tumors.

Computational Modeling Identifies Key Processes in Growth of Pancreatic Cancer Precursor Lesions

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

Gene sequence features brightly colored squares against a black background; shows genes in the human genome.

NCI-Funded Tool Helps Characterize Noncoding Elements that Impact Cancer Genes

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.

Double helix DNA molecule is shown in three dimensions set against a background of blue and gold.

Analysis Tool Aids in Identifying Genes that Hijack Enhancers

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.

Digitized DNA strand on hi tech future blue background.

NCI ITCR Investigators Develop New Tool for Analyzing Copy Number Variations Across the Genome

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

Chromosomes are shown in a three-dimensional illustration. Yellow caps on the tips of the chromosomes denote telomeres.

NCI-Funded Researchers Develop Tool for Deciphering Telomeres

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.

GammaGateR helps identify biomarkers in multiplexed immunofluorescence images. Image shows markers in red and blue within a single slide sample.

GammaGateR Helps Decipher Imaging Data

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.

Multimodal image of cancer tumor cells shows how the Orion tool is able to combine two types of images—hematoxylin and eosin and immunofluorescence—in a single slide.

NCI-Funded Tool Combines Imaging Modalities to Aid Pathologists and Machine Learning (ML)

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.

A hand is holding a tablet. Illuminating from the table is the image of a clock. This abstract image conveys how technology is helping monitor disease and predict the course of cancer over time.

AI, Genomics, and Clinical Data Help Track Cancer’s Evolution Over Time

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.

Image displays timeline of diverging treatment schedules seen for different patients. 1. is a computer with a data chart. 2. Data from patients goes into the cloud. 3. Data is analyzed. 4. Treatment options are produced based on data research.

NCI Study Shows Promise of Machine Learning’s Role in Personalized Cancer Treatment

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.

MRI image of an enlarged prostate.

NCI Uses AI to Take the Guesswork Out of Assessing Prostate Cancer Images

NCI researchers are using artificial intelligence (AI) to uncover additional information from medical images. This helps them not only to diagnose cancer but also to predict how it will progress and if it will re-occur.

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