# Computational Genomic Epidemiology of Cancer (CoGEC) Training Program

> **NIH NIH T32** · CASE WESTERN RESERVE UNIVERSITY · 2024 · $227,204

## Abstract

PROJECT SUMMARY/ABSTRACT
Undertaking innovative cancer research requires input from teams of scientists with a mixture of backgrounds,
including molecular biology, oncology, medicine, epidemiology, biostatistics, genomics/genetics,
bioinformatics, computer science and artificial intelligence. Researchers with interdisciplinary training across
these fields are extremely valuable to such teams, as they can act as conduits for the integrated work
necessary to accomplish some of the most promising and forward-looking cancer research. Due to the
exclusive nature of training within these fields, however, there are limited opportunities for investigators to
obtain the knowledge that bridges these disciplines. To help remedy this problem, we propose here the
continuation of this T32 program to provide postdoctoral training in the Computational Genomic Epidemiology
of Cancer (CoGEC) at the Case Comprehensive Cancer Center. The CoGEC training program defines a novel,
transdisciplinary area of training at the intersection of cancer research, epidemiology, biostatistics, genetics,
and computer science. The program’s structure is defined by three key requirements. First, all trainees will
have the opportunity to take a specialized core curriculum of five courses to fill in the gaps of their previous
training if necessary. Second, the trainees will undertake additional didactic experiences selected to
complement their educational and research background. Third, all trainees will obtain research experience by
collaborating with multiple mentors on high-level computational genomic epidemiology of cancer projects. As
an extension of this research experience, each trainee will be required to write and defend an NIH grant
proposal. Cancer researchers obtaining training in this program will have the skills vital to deciphering the
complex pathways comprising genetic and environmental risk factors for disease. In doing so, their knowledge
and findings will be translated into improved cancer understanding, prevention and treatment.

## Key facts

- **NIH application ID:** 10916175
- **Project number:** 5T32CA094186-22
- **Recipient organization:** CASE WESTERN RESERVE UNIVERSITY
- **Principal Investigator:** Thomas Louis LaFramboise
- **Activity code:** T32 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $227,204
- **Award type:** 5
- **Project period:** 2017-08-01 → 2028-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10916175

## Citation

> US National Institutes of Health, RePORTER application 10916175, Computational Genomic Epidemiology of Cancer (CoGEC) Training Program (5T32CA094186-22). Retrieved via AI Analytics 2026-05-26 from https://api.ai-analytics.org/grant/nih/10916175. Licensed CC0.

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