# Cancer Informatics Shared Resource

> **NIH NIH P30** · UNIVERSITY OF MINNESOTA · 2024 · $287,564

## Abstract

Cancer Informatics Shared Resource Summary
Modern cancer research critically depends on advanced computing, data analysis, and modeling for the
generation of basic and translational experimental data; harmonization, secure storage, and retrieval of clinical
data; clinical-molecular data integration; and interpretation, annotation, and integration of results. The Cancer
Informatics Shared Resource (CISR) provides Masonic Cancer Center (MCC) members with cutting-edge
multi-omics data analytics and translational data science, advanced natural language processing research and
application development, data storage infrastructure, and expert consulting and collaboration to support all
aspects of their research.
CISR is a combination of the previous Bioinformatics and Clinical Informatics Shared Resources. It is led by
Dr. Jinhua Wang, a Full Professor in the University of Minnesota Institute for Health Informatics and a
computational biologist with research interests in computational modeling of high-throughput cancer multi-
omics data. He is supported by Dr. Scott Walmsley, who was recruited to lead proteomics/DNA adductomics
informatics, and Dr. Steven Johnson, who heads the Clinical Informatics Shared Service (CISS). Additional
staff were recruited or promoted, and a genomics data repository was built to link genomic information with
clinical health records.
CISR will achieve its mission through 5 specific aims: 1) Support MCC researchers with advanced capabilities
in cancer multi-omics informatics and clinical data science and analytics, through a FAIR and artificial
intelligence/machine learning–ready data environment; 2) Pursue development of new methods in the areas of
single-cell multi-omics, spatial transcriptomics imaging, and AI deep learning predictive models for cancer
research; 3) Enhance clinical trial recruitment via data-driven understanding of the factors determining accrual
success and decision models to enhance accrual; 4) Develop and provide integration infrastructure and
methods towards developing cancer patient Digital Twins to support predictive oncology research and patient
care; and 5) Provide education and training in multi-omics data analytics, spatialomics data integration, and
precision oncology.
CISR also has close collaborations with the Clinical Trials Office, Translational Therapy Shared Resource,
Biostatistics Shared Resource, and the Cancer Research Translational Initiative within MCC, as well as with
the Institute for Health Informatics and the Clinical and Translational Science Institute in the larger University
community.
In fiscal year 2022, 47 individuals used CISR services, of whom 41 were MCC members.

## Key facts

- **NIH application ID:** 10768160
- **Project number:** 2P30CA077598-26
- **Recipient organization:** UNIVERSITY OF MINNESOTA
- **Principal Investigator:** Jinhua Wang
- **Activity code:** P30 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $287,564
- **Award type:** 2
- **Project period:** 1998-06-01 → 2029-01-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10768160

## Citation

> US National Institutes of Health, RePORTER application 10768160, Cancer Informatics Shared Resource (2P30CA077598-26). Retrieved via AI Analytics 2026-05-27 from https://api.ai-analytics.org/grant/nih/10768160. Licensed CC0.

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