# Big Data Training for Cancer Research

> **NIH NIH R25** · PURDUE UNIVERSITY · 2020 · $238,709

## Abstract

PROJECT SUMMARY
The increasing volume of big data in cancer research has the potential to dramatically accelerate the translation
of knowledge from bench to bedside. Unfortunately, most cancer researchers are unable to: (i) utilize the valuable
big data that is readily available in the public domain, and (ii) extract knowledge from cancer big data through
communicating with computer scientists, statisticians and bioinformaticians. Traditionally, cancer researchers
are trained in the biologically related sciences that are relevant to the manifestation of the disease. This
knowledge is, and remains, critical for understanding the biological and molecular mechanisms that result in the
disease and that can be targeted for clinical intervention. However, historically, cancer researchers have not
been trained to handle large volumes of data. There was no need; there were not many approaches that were
generating large scale data. Yet, with the advent of high-throughput approaches, in particular those related to
genomics, proteomics and metabolomics, a significant gap in the training of cancer researchers has become
apparent – the need for skills in computer science and statistics to analyze big data and interpret results from
the analyses. In the absence of quantitative training for cancer researchers, a bottleneck will remain in the
translation of the large body of cancer big data to clinical practice. This need was confirmed in a needs
assessment of researchers from 95 Cancer Centers sent out last year (including all 69 NCI-Designated Cancer
Centers).
To address the need for a big data training course, the investigators propose to build on a previously NIH-funded
big data training course, to develop and deliver a new training course tailored to cancer researchers across the
country. In a partnership between the Purdue University Center for Cancer Research (PCCR), the Indiana
University Simon Cancer Center (IUSCC), and a group of traditionally trained biostatisticians, the team is in a
unique position to leverage basic and clinical cancer centers (the only two NCI-Designated Cancer Centers in
the State), to work together on this multi-disciplinary training program. In contrast to the previous successful big
data training course designed for general biomedical researchers who were novices in big data science, this new
course will target cancer researchers with the knowledge of big data value but lacking the quantitative skills
necessary to work with it. Based on case studies from both PCCR and IUSCC researchers, the goal of the
course is to help participants develop skills for managing, visualizing, analyzing, and integrating various types
of cancer big data that are publicly available. This is increasingly important as more and more precision oncology-
focused treatments are coming on line. With this customized big data training, cancer researchers can realize
the transformative potential of big data by translating it from bench to bedside.

## Key facts

- **NIH application ID:** 10019476
- **Project number:** 5R25CA233429-02
- **Recipient organization:** PURDUE UNIVERSITY
- **Principal Investigator:** MIN ZHANG
- **Activity code:** R25 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $238,709
- **Award type:** 5
- **Project period:** 2019-09-17 → 2024-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10019476

## Citation

> US National Institutes of Health, RePORTER application 10019476, Big Data Training for Cancer Research (5R25CA233429-02). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10019476. Licensed CC0.

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