News

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

CCDI additions include molecular characterization data from childhood cancer patients of racial and ethnic diversity.

NCI is soliciting feedback on the utility and future promise of multidimensional tumor atlases for the Human Tumor Atlas Network, including high-priority data types and challenges/opportunities for computational modeling. Your responses are due January 7, 2023.

Data analysis of the DNA, RNA, protein, and phosphoprotein in lung adenocarcinoma cells connected molecular features of tumors with patient survivability. This study allowed researchers to better predict prognosis and treatment in lung cancer patients.

The latest updates for NCI Enterprise Vocabulary Services include terminology sets for NCI’s Genomic Data Commons, CDISC’s Digital Data Flow project, and a new edition of the NCI Metathesaurus.

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.

Share your thoughts on how data science can impact cancer’s toughest challenges, and your idea could transform into a team-operated, funded project for resolving that challenge! The deadline is November 28, 2022.

This newly released data set provides imaging in pediatric patients with newly diagnosed primitive neuroectodermal tumors throughout their treatment and until any potential relapse.

A new $14 million project, funded by NIH’s Bridge2AI program, is turning the traditional biomarker concept on its ear. Instead of examining genetic or similar molecular characteristics, researchers are collecting data to look for voice biomarkers that can be linked to cancer.

Explore the newly released pediatric data set that includes information on DNA/RNA sequencing, methylation arrays, and deidentified clinical reports.

Learn more about NCI’s Request for Information and contribute to the conversation around cancer metabolomics data.