Center for Biomedical Informatics and Information Technology
The Center for Biomedical Informatics and Information Technology's (CBIIT) mission is to empower NCI staff and the cancer research community with the data science, information technology, and data sharing tools they need to advance our knowledge of cancer. CBIIT's vision is to accelerate ground-breaking research using data and technologies to minimize the burden of cancer.
Focus Areas
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NCI Data CatalogCollection of data listings by major NCI initiatives and other data sets.
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ProjectsExplore several of our collaborations throughout the cancer community.
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Data Science TrainingLearn more about the inter-disciplinary field of data science.
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Vocabulary for Cancer ResearchLearn essential cancer vocabulary to support clear communication.
Recommended Events
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Theranostics and Digital Twins for Personalized Medicine
Jan. 14, 2026 | 11:00 a.m. ET | Attend this Data Science Seminar to learn about the intersection of two critical data science concepts in cancer research: theranostics and digital twins.
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XNAT Scout: Enabling Translational AI
Jan. 22, 2026 | 11:00 a.m. ET | Attend this webinar to learn about XNAT Scout—an extension of the XNAT imaging informatics platform that’s designed to close the gap between artificial intelligence model development and clinical deployment.
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Data Driven QSP Modeling of Cancer
March 6, 2026 | 11:00 a.m. ET | Learn how an NCI-funded, data-driven QSP model could help predict cancer treatment response.
News
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New Data from CCDI's Pediatric in Vivo TestingCCDI just released molecular characterization data that may help your research.
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Navigating the 2024 NIH Public Access PolicyNIH is updating its Public Access Policy to ensure free, immediate access to taxpayer-funded research.
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AI Model for Prostate Cancer Show Feasibility in Clinical SettingA new study tests using AI on a public platform to detect prostate cancer in MRI scans.
Cancer Data Science Pulse Blog
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Many Hands Make Light Work: Your Role on a Cancer Data Science Research TeamA multidisciplinary team consists of many different responsibilities. Where do you fit in?
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Lessons Learned from Project MATCHCBIIT team shares the lessons they learned in modernizing and automating the platform for tracking and managing these patients, along with their samples, and other research data.
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The Making of a Machine Learning (ML) Robotics Tool: IMMUNOtronMeet IMMUNOtron, a ML-robotic platform that’s helping NCI researchers generate and process high-quality data to better understand the immune system’s response to cancer.