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

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.

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.

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.

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.

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

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.

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.

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.

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.

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.