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Data Science & Engineering Research Group

abstract and blurred graphs on a green background, representing data science

The DCEG Data Science & Engineering Research Group (DSERG) seeks to advance research and infrastructure for data-intensive precision prevention studies. The primary goals of the Group are to:

Data Science & Engineering Research Group (DSERG)

Jonas Almeida, Ph.D. - Group Director and senior investigator

Staff Directory - DSERG Members

We are hiring! Check out our research training opportunities.

Meet current fellows in DSERG

  • Accelerate the investigation of the causes of cancer
  • Advance cloud computing infrastructure for precision prevention
  • Develop transdisciplinary human capital through weekly Cloud4Bio Hackathons at the NCI Shady Grove campus

Research Areas and Topics of Interest

EpiSphere

EpiSphere is an online environment for web-based tools to operate in the Cancer Epidemiology Commons.

FeatureScape

FeatureScape is an interactive representation and analysis of feature landscapes.

Serverless OpenHealth

Artist's conception of how NCI fellowships help to grow data scientists. Shows drawing of two men and two women standing in separate flowerpots with a watering can overhead.

Growing the Field: Fellowships in Data Science

Dr. Monjoy Saha discusses the value of data science training at the NCI

Serverless OpenHealth supports large-scale interactive data access and analysis entirely through the web computing environment. Serverless OpenHealth (PubMed abstract)

See a live demo of Serverless OpenHealth

The Connect for Cancer Prevention Study

The Connect for Cancer Prevention study is a "next-generation" cohort study based in integrated healthcare systems. The goal is to enroll 200,000 adults in the United States to further investigate the etiology of cancer and its outcomes, which may inform new approaches in precision prevention and early detection.

The Confluence Project

The Confluence Project is a research resource currently under development, designed to uncover breast cancer genetics through genome-wide association studies (GWAS). The study will include at least 300,000 breast cancer cases.

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