Center for Biomedical Data Science
Using big data to detect and treat diseases earlier, faster, and better.
Research and Funding Opportunities
CBDS empowers researchers across Oregon to unite and use big data to prevent and cure deadly diseases like cancer. We support collaborative teams in developing and applying cutting-edge data science tools, including AI and machine learning, and training the next generation of biomedical data scientists.
Current Research Priorities |
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Multi-omics data integration and analysis using machine learning: Utilizing deep learning to analyze complex, multi-omics datasets, including transcriptomics, proteomics, secretomics, and metabolomics, to uncover fundamental principles of cell and tissue biology in health and disease. |
Artificial intelligence innovations in biomedical image analysis: Applying artificial intelligence to analyze large imaging datasets for biological abnormalities, such as pathology or injury. Innovative approaches in image analysis will be prioritized, particularly those that enhance detection and screening capabilities. |
Aging as a unifying theme in cancer: Applying deep learning to model aging across biological scales - cells, tissues, and whole organisms - and to explore its relationship to cancer. |
Immunodiscovery, immunoengineering and immunotherapy: Utilizing data science to explore the immune system, and how it relates to disease and progression. |
Innovation in these scientific areas relevant to cancer research involving:
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Acknowledgement and Publications
Published research, including articles, preprints and books resulting from projects supported by CBDS must carry the following acknowledgment: “This work was supported by a grant from the Center for Biomedical Data Science (CBDS)”.
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