Preterm Birth Prediction – Microbiome
Learn More Goal To develop predictive models for risk of preterm birth in pregnant individuals based on vaginal microbiome data. There is
scRNA-seq and scATAC-seq Data Analysis
Learn More Understanding transcription signals at the individual cell resolution is fundamental to our understanding of more complex biological systems such as
Predicting Gene Expression Using Millions of Random Promoter Sequences
Learn More Decoding how gene expression is regulated is critical to understanding disease. Regulatory DNA is decoded by the cell in a
Anti-PD1 Response Prediction Dream Challenge
LEARN MORE While durable responses and prolonged survival have been demonstrated in some lung cancer patients treated with immuno-oncology (I-O) anti-PD-1 therapy,
COVID-19 EHR DREAM Challenge
LEARN MORE The rapid rise of COVID-19 has challenged healthcare globally. Due to the importance and emergent need for better understanding of
CTD2 Chemosensitivity DREAM Challenge
Learn More The Columbia CTD2 Center developed PANACEA (Pancancer Analysis of Chemical Entity Activity), a comprehensive repertoire of dose response curves and
Metadata Automation DREAM Challenge
Learn More We aim to significantly lower the burden of adding coherent metadata annotations across the data ecosystem to streamline and enable
BEAT-PD DREAM Challenge
Learn More Recent advances in mobile health have demonstrated great potential to leverage sensor-based technologies for quantitative, remote monitoring of health and
CTD^2 BeatAML DREAM Challenge
Learn More The goal of the Beat AML DREAM Challenge is to define patient subpopulations tailored to individual treatments by discovering (genomic
CTD^2 Pancancer Drug Activity DREAM Challenge
Learn More Over the course of two years, the Columbia CTD2 Center developed PANACEA (Pancancer Analysis of Chemical Entity Activity), a comprehensive