# Computational Sciences Shared Resource

> **NIH NIH P30** · JACKSON LABORATORY · 2020 · $261,032

## Abstract

PROJECT SUMMARY COMPUTATIONAL SCIENCES
The JAX Computational Sciences (CS) Shared Resource is central to the achievement of the JAX Cancer
Center's (JAXCC) scientific program objectives. As cancer research has become increasingly data intensive, it
is vital that investigators be capable of interpreting and leveraging vast data sets, both publicly available and
internally generated, to understand tumor biology. Such data analysis requires access to a dynamic suite of
analytical tools; infrastructure supporting those tools; computational, bioinformatic and statistical expertise to
mine and analyze the data; and quantitative analysts and software engineers to develop and build queries and
algorithms. Established in 1998, CS has been operating as a shared resource within the JAXCC since 2001 but
was dramatically expanded in 2013. The 41 member CS group addresses faculty needs by providing in-depth
expertise to JAXCC members in support of their independent research projects. This includes guidance in
experimental design; support for the integration of multi-platform data sets, data analysis software applications
and database development; development and application of computational procedures, statistical methods and
scientific software; and project management. CS also provides training and mentorship opportunities in
computational cancer research approaches and manages a plethora of analysis pipelines essential for cancer
genomic research conducted by JAXCC members. Staff include a multi-disciplinary mix of computational
biologists, computer scientists, statisticians, bioinformatics software engineers, and research project managers,
who bring significant depth of expertise in cancer genomics, metabolomics, biostatistics, software development,
machine learning, single cell genomics and integrative analysis, consistent with the needs of JAXCC members.
CS' three operational groups (Statistics and Analysis, Scientific Computing, Research Project Management) are
housed on the Bar Harbor, ME and Farmington, CT campuses, and each supports JAXCC members on both
campuses. Functioning in a modular manner, PIs can access the right mix of experienced expertise tailored to
their scientific needs. The Specific Aims for CS are: 1) To support JAXCC members in developing cutting-edge
analytical procedures for emerging problems in cancer genomics, and to carry out integrative analysis in
fundamental and translational cancer research; 2) To develop bioinformatics applications, maintain scientific
analysis workflows, and provide data architecture and software engineering expertise for the development and
management of scientific data portals pertaining to specific scientific questions addressed by JAXCC members;
and 3) To assist in resource planning for and management of complex computational projects and long-term
information technology and data science development for JAXCC members.

## Key facts

- **NIH application ID:** 9854056
- **Project number:** 2P30CA034196-34
- **Recipient organization:** JACKSON LABORATORY
- **Principal Investigator:** Jeffrey Hsu-Min Chuang
- **Activity code:** P30 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $261,032
- **Award type:** 2
- **Project period:** — → —

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9854056

## Citation

> US National Institutes of Health, RePORTER application 9854056, Computational Sciences Shared Resource (2P30CA034196-34). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/9854056. Licensed CC0.

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