# Data Sciences and Informatics

> **NIH NIH P30** · UNIVERSITY OF PENNSYLVANIA · 2022 · $233,661

## Abstract

PROJECT SUMMARY
The major focus of Core C, the Data Science and Informatics (DSI) core, is to facilitate human discovery
through basic and translational research in cutaneous biology and disease by providing assistance to
investigators on the planning, design, and analysis (both statistical and informatics) of studies of the skin. The
DSI interacts directly with the other Resource Cores and the overall theme of the SBDRC in that bench and
human translational research needs to be well designed, properly conducted, and correctly analyzed in order
to maintain high standards of rigor and reproducibility. DSI achieves these goals by a combination of
epidemiologic, statistical and informatics approaches. By its very nature, DSI will continue to be highly
collaborative and will add value to the other cores. DSI Core directors will encourage investigators interested in
cutaneous research to work with Core faculty and staff at every stage of design and analysis, thus promoting a
team science approach from hypothesis inception to study execution, analysis, and interpretation. DSI’s
functions are represented by two Aims that leverage expertise of Core faculty and staff in the following areas:
Aim 1: To provide study design and biostatistical services to SBDRC Core users, including: 1) Study design
methodologies necessary to design and implement rigorous experimental and clinical investigations; 2)
Statistical methodologies critical for the evaluation of each project’s research hypotheses including
consideration of sex as a biologic variable; 3) Interpretation of research data to make scientifically and
statistically appropriate statements; 4) Translation of bench findings to human research using translational and
clinical trial designs. Aim 2: To provide biomedical informatics & computational dermatology services to
SBDRC Core users, including: 1) Bioinformatics approaches to allow for the analysis and conceptualization of
large genomic and metagenomic datasets; 2) Artificial intelligence-guided approaches to quantify patterns and
textures in microscopy images; 3) Medical informatics approaches to query medical records databases from
UPHS and extramural sources. A critical barrier to progress in cutaneous biology and skin disease research is
the lack of integration of biostatistical, epidemiological (both quantitative and qualitative), and informatics
approaches to basic and clinical investigation. DSI will significantly add to the overall success of the SBDRC by
addressing this barrier and the specific need for these approaches in human translational research.
Implementing such approaches from inception through project completion will improve the reproducibility, rigor,
and validity of research findings. The other SBDRC Resource Cores and the Administrative Core will be able to
leverage the expertise of DSI faculty and staff to enhance the efficiency, reproducibility, and validity of research
promoted by the SBDRC.

## Key facts

- **NIH application ID:** 10477235
- **Project number:** 5P30AR069589-07
- **Recipient organization:** UNIVERSITY OF PENNSYLVANIA
- **Principal Investigator:** David Joel Margolis
- **Activity code:** P30 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $233,661
- **Award type:** 5
- **Project period:** 2016-09-15 → 2026-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10477235

## Citation

> US National Institutes of Health, RePORTER application 10477235, Data Sciences and Informatics (5P30AR069589-07). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10477235. Licensed CC0.

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