News

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

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New NCI-Supported Platform for Open Data Challenges

Explore a resource that lets you search for data challenges that address areas of unmet medical need!

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Sharing Cancer Research Software? NIH Wants to Hear from You!

Are you working with source codes, algorithms, workflows, and other software in your cancer research? NIH wants to hear from you! Respond today to help NIH develop new best-practice guidelines.

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Looking to Improve the Processes Around Real-World Data? Share Opinions with NIH!

NIH wants to hear from you! Give your perspective on how to better use Real-World Data in biomedical and behavioral research.

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Two NCI Fellowship Opportunities Available in Computational Biology and Bioinformatics

Check out these paid predoctoral and postdoctoral fellowship opportunities at NCI’s Center for Cancer Research.

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Meet MOPAW—A New Tool for Using Multi-omics Data in NCI’s Cancer Genomics Cloud

Want to use multi-omics data to examine different genetic pathways underlying cancer, but you lack the necessary coding experience? Meet MOPAW, a new point-and-click interface that can help you make the most of your genetic data.

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NCI’s Imaging Data Commons Helps Address Challenges in Computational Pathology

Having trouble reproducing results from machine learning (ML) computational pathology studies? See how NCI’s Imaging Data Commons may be able to help, as evidenced by a new study.

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The Childhood Cancer Data Initiative (CCDI) Releases ‘Explore Dashboard’ to Make Data More Findable

Do you use CCDI-managed data? Check out the CCDI Hub Explore Dashboard, a tool that allows you to discover CCDI-managed data and connect with participants and available samples and files.

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Apply for a Postdoctoral Fellow Position in Computational Biology

Come work at NCI's Center for Cancer Research (CCR)! Apply to work with CCR Deputy Director Dr. Xin Wei Wang and study genetics, genomics, and biochemical pathways related to liver cancer.

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New Approach Helps Address Lack of Diversity in GWAS Cancer Data

In a recent study, NCI’s Dr. Haoyu Zhang describes CT-SLEB—a powerful and computationally scalable method for generating more precise polygenic risk scores across a range of ancestral groups (including Latino, African American, East Asian, and South Asian).

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Deadline Extended: Tell Us if NCI Cancer Research Data Commons’ Data are Compatible with AI

NCI wants your input to help determine how compatible NCI’s Cancer Research Data Commons is with artificial intelligence applications. Explore this request for information to learn how to contribute!

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