# Data Science Facility Core

> **NIH NIH P30** · TEXAS A&M UNIVERSITY · 2022 · $319,341

## Abstract

DATA SCIENCE FACILITY CORE (DSFC) ABSTRACT
The proposed Texas A&M Center for Environmental Health Research (TiCER) is focused on “Enhancing
Public Health by Identifying, Understanding and Reducing Adverse Environmental Health Risks.” The Data
Science Facility Core (DSFC) will provide key enabling services in data collection, storage, analysis, and
integration to assist members of the Center to fulfill this mission. Key data science challenges that the DSFC
will address include the high dimensionality of novel biological and chemical data streams, the mixture of
structured and unstructured data at the level of local communities, and the need to translate data into
actionable knowledge for environmental health decision-making. The DSFC will support these needs by
leveraging data science expertise and resources across Texas A&M. There is a nearly ubiquitous need for
such services across the Center’s four research themes: Stressors to Responses; Environment and
Metabolism; Individuals to Populations; and Community, Regulation, and Policy. Thus, the DSFC will serve as
a key facilitator of interactions across the entire Center. The DSFC’s overarching goals are to provide novel
and state-of-the-art data science services to support and integrate the Center’s scientific and outreach
activities. This goal will be accomplished by providing services in several specialized and complex areas of
data science—computational toxicology, bioinformatics, and statistics/biostatistics—as well as providing a
central data repository for Center investigators. In the computational toxicology area, the focus will be on
characterizing and predicting chemical toxicity through both mechanistic and data-driven
mathematical/statistical models that integrate multiple diverse data sets. In the bioinformatics area, emphasis
will be placed on guiding investigators in navigating the many available commercial and open-source analysis
options, developing customized analytical workflows, and addressing any needs for new methods
development. Statistics and biostatistics support will be provided both for basic services such as study design
and routine analysis, as well as for custom needs for collecting, processing, integrating, and drawing
conclusions from diverse data sets. Integration of data will be facilitated through a common data repository,
the design and development of which will be closely coordinated with the rest of the Center, and which be
indexed for searching and data mining. The DSFC will provide these services through a flexible combination of
direct support from Core personnel and vouchers to allocate as needed ($138,000/year from NIEHS and
$20,000/year from Texas A&M commitment). The DSFC will work closely with the Administrative Core to
encourage investigators’ use of the DSFC and access and track the Core’s operation and funding allocations.
The leaders of the DSFC have an established track record of collaborative, interdisciplinary, and translational
research, and a...

## Key facts

- **NIH application ID:** 10400883
- **Project number:** 5P30ES029067-04
- **Recipient organization:** TEXAS A&M UNIVERSITY
- **Principal Investigator:** Weihsueh A Chiu
- **Activity code:** P30 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $319,341
- **Award type:** 5
- **Project period:** 2019-05-01 → 2024-03-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10400883

## Citation

> US National Institutes of Health, RePORTER application 10400883, Data Science Facility Core (5P30ES029067-04). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10400883. Licensed CC0.

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