# Cancer Informatics Shared Resource

> **NIH NIH P30** · UNIVERSITY OF WISCONSIN-MADISON · 2021 · $466,855

## Abstract

PROJECT SUMMARY / ABSTRACT 
The Cancer Informatics Shared Resource (CISR) operates out of the University of Wisconsin (UW) 
Department of Biostatistics and Medical Informatics (BMI) to serve University of Wisconsin Carbone Cancer 
Center (UWCCC) members. Our mission is to promote high quality, innovative cancer research by providing 
members of the UWCCC with bioinformatics and computational expertise and services, including the design of 
experiments, analysis of research and clinical data, development of tools for analysis and visualization, and 
interpretation of results. This is achieved through CISR's well-qualified staff: three PhD staff scientists with 
expertise in state-of-the-art bioinformatics, clinical informatics, and machine learning methodologies; and four 
highly skilled faculty, who mentor the CISR scientists and collaborate with UWCCC members in cases where 
new algorithm development is required. CISR continues to advance in its essential role to meet the evolving 
needs of all UWCCC programs by providing a technical and intellectual resource that addresses the specific 
bioinformatics and clinical research informatics needs of UWCCC members across all six programs in a 
reliable and cost-effective manner. CISR accomplishes this through two specific aims, the first of which is a 
new enhancement made during the most recent CCSG funding cycle in direct response to requests from the 
UWCCC membership and advice from our advisory committee. Our specific aims are to: 1) provide state-of- 
the-art Informatics services: image analysis, bioinformatics, cancer genomics, predictive analytics, clinical 
informatics to facilitate study design and grant applications, and to employ programs to correlate, stratify, and 
discover patterns from research and clinical data sets using state-of-the-art informatics and machine learning 
algorithms; and 2) provide world-class Informatics Algorithm/Methodology Development by each of four faculty 
members with expertise in the development of novel algorithms in areas such as machine learning, electronic 
health record analysis, causal discovery from observational data, natural language processing, deep learning 
and knowledge-based artificial neural networks, and RNA-Seq gene expression data analysis. Together, CISR 
scientists and faculty are agile and have the availability and expertise required to enable UWCCC members to 
quickly investigate new hypotheses for grant submissions, analyze research or clinical data for publication, as 
well as tackle more challenging, unsolved research questions which require longer-term research. Funding 
provided by CCSG will ensure that our team of CISR scientists and faculty will continue to be well positioned to 
meet the bioinformatics and computational research needs of UWCCC investigators to enable discoveries that 
can improve outcomes for our patients.

## Key facts

- **NIH application ID:** 10147661
- **Project number:** 5P30CA014520-47
- **Recipient organization:** UNIVERSITY OF WISCONSIN-MADISON
- **Principal Investigator:** Colin Noel Dewey
- **Activity code:** P30 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $466,855
- **Award type:** 5
- **Project period:** 1997-04-25 → 2023-03-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10147661

## Citation

> US National Institutes of Health, RePORTER application 10147661, Cancer Informatics Shared Resource (5P30CA014520-47). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10147661. Licensed CC0.

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