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

With the help of machine learning, NCI-funded researchers were able to boost the prognostic power of a common blood test for liver cancer.

NCI-funded researchers used machine learning to characterize a cancer biomarker based on exosomes. Their biomarker worked well using non-invasive sources, such as blood and urine, allowing the researchers to catch cancer early, even in tumors of undetermined origins.

Do you conduct research on statistical and analytical methods, cancer survivorship, digital health, and/or data science tools and methods? Apply for an R01 grant from NCI’s Division of Cancer Control and Population Sciences by June 5 or October 5, 2024.

A new algorithm is showing promising results in predicting lung cancer. See how proteins in your blood may someday help determine your risk for lung cancer.

This Notice of Funding Opportunity will allow you to create and run a short course to educate early career researchers on using data sets available in NIH’s Common Fund.

PepQuery2 is a proteomics tool that enables rapid and targeted identification of both known and novel peptide sequences in proteomics data sets. The tool aims to provide valuable data sets for the broader research community by making public proteomics data more accessible and user-friendly.

NCI-funded researchers have developed a new artificial intelligence algorithm that’s helping identify the underlying biological causes of glioblastoma.

Support the maintenance and enhancements of the Clinical Proteomic Tumor Analysis Consortium (CPTAC) Assay Portal, including the assay characterization data within it, through a new contract opportunity. Your proposal is due March 28, 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 update to the Childhood Cancer Data Catalog includes website improvements and the addition of the database of Genotypes and Phenotypes (dbGaP).