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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.

Abstract image of a round, purple cell surrounded by a blue nebulous background.

Deadline Extended: Submit Your Abstract for the Ninth Computational Approaches for Cancer Workshop by August 14

CAFCW23 brings together data and computational scientists, cancer biologists, and developers interested in accelerating the progress of computationally and data-driven cancer research and clinical applications.

Stylized image shows a strand of DNA next to a drawing of a liver. Illustrates the idea that DNA may aid in detecting liver cancer.

DNA Fragmentome Data—A New Omics AI Technology for Detecting Cancer

NCI-funded researchers validated a genome-wide artificial intelligence technology that could help in early detection of hepatocellular carcinoma—the most common type of liver cancer.

Illustration of DNA helixes in different shades of blue.

NCI SBIR Helps Tech Company Take Next Steps in Precision Medicine Platform via Digital Twins

With help from NCI’s Small Business Innovation Research (SBIR) program, researchers are refining a biophysical simulation technology using computational models for personalized cancer care.

Artists conceptualization of a digital twin. Shows the mirrored image of two heads. The only difference is one head is filled in with dots whereas the second head has spaces missing.

Cancer Patient Digital Twins—A Progress Report and Next Steps

Collaboration, cooperation, and the need for multimodal, multiscale data were central themes in a recent article on NCI’s efforts to develop a cancer research digital twin.

Stylized graphic showing a DNA double helix

CLIM: A Data Science Approach to Identifying “Bystander” Genes in Cancer Precision Medicine

A new precision medicine platform combines machine learning with sophisticated analysis to help researchers mine chromosomal alterations linked to cancer.

Two technology experts working in a server room. A female wearing business attire is looking over a laptop with her colleague, a male in casual business attire pointing at the screen.

Deadline Extended: Submit Abstracts for the Eighth Computational Approaches for Cancer Workshop by August 16

As the necessity for and availability of large data sets in cancer applications grows, so do the challenges when conducting research and clinical applications with computational solutions. Share your experience with how to address such challenges.

Cancer drug target visualized at the atomic level, the protein p97 is trapped in an inactive state by a new inhibitor (red) and the molecule cannot proceed into its normal reaction cycle. Image created using cryo-electron microscopy.

New NCI-DOE Collaboration Project, IMPROVE, Seeks Deep Learning Model Approaches

IMPROVE focuses on improving deep learning models to predict the efficacy of cancer treatments. The research community, including data scientists and informaticists, is asked to respond to an RFI for creating protocols to evaluate model performance by April 15, 2022, at 5:00 p.m. ET. Additionally, they are encouraged to respond to an RFP for improving model comparison by May 9, 2022.

Tumor cells (colored red and brown) are shown in 3-dimensions against a black background. The cells are close together, emphasizing the importance of cell-cell interactions in supporting tumor growth.

Machine Learning Modeling Generates Accurate Insights into RAS-membrane Biology

In RAS-related diseases, such as cancer, mutations in the RAS genes or their regulators render RAS proteins persistently active. Investigating RAS activation events is challenging when using conventional techniques. An unprecedented multiscale platform is using machine learning to change that.

Image of a cloud made up of different container technology icons (i.e. docker, snakemake)

Learn More About the Cloud and Container Technology Driving Cancer Data Science at the Containers and Workflow Interest Group (CWIG) Webinars

The relaunched monthly CWIG webinar series will invite researchers from across the globe to discuss the latest advancements in cloud computing technologies, workflow, tools, and packages.

Promotional banner with a silhouette of a human (composed of ones and zeroes) with a 3D model of a cell. Text reads, "Computational Approaches for Cancer Workshop. CAFCW21. November 14, 2021."

Submit Abstracts for the Seventh Computational Approaches for Cancer Workshop

Data scientists, cancer biologists, and computational scientists are invited to submit abstracts to the Computational Approaches for Cancer Workshop (CAFCW21). Papers should focus on the application of computational approaches to cancer challenges, and those selected will be presented at the workshop. Abstract submissions are due by Monday, September 13.

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