# Data Science & Management Core

> **NIH NIH P01** · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · 2021 · $434,998

## Abstract

ABSTRACT
Data Science & Management Core (Timothy Verstynen, CL)
This Program Project aims to explicate the neurobiology of behavioral and socio-environmental influences on
risk for cardiovascular disease (CVD) in midlife adults. Meeting the special analytic demands of the Program
Project requires integrating traditional statistical approaches with cutting-edge machine learning and data
science tools for large, high-dimensional data sets (i.e., multivariate neuroimaging, biological, and behavioral
data collected at multiple time points). Accordingly, Core C is tailored to these novel analytical challenges.
Specifically, the integrative approach of Core C consists of combining approaches that can (i) identify specific
functional or structural brain networks from hundreds of thousands of measurements across the brain that
reliably predict biological, behavioral, and cardiovascular health-related variables and (ii) generate appropriate
metrics from these brain measurements that can be integrated into structural equation models that use neural,
behavioral, and physiological factors to predict changes in mediators and markers of CVD risk over time. To
this end, Core C will employ: (i) experts in machine learning, multi-level modeling methods, and biostatistics
for generating brain phenotype metrics (Aim 1) and developing prospective models of CVD risk emergence
(Aim 2); and (ii) experienced data managers to develop protocols for the secure collection and maintenance of
Project data (Aim 4). Core C will also work with the Administrative Core (Core A) to ensure efficient flow of
data through the Program Project by providing regular updates on the receipt of data from the Measurement
Core (Core B) and the 3 Projects (Ps), as well as data distribution to each P. Under the leadership of Dr.
Timothy Verstynen (a doctorally-trained cognitive neuroscientist with advanced expertise in quantitative
modeling and machine learning) and as reinforced by the coordinating efforts of Dr. Aarti Singh (a statistician
and authority in machine learning), Core C will (i) provide centralized research support, (ii) provide advanced
statistical expertise and harmonize data analyses; (iii) consult on novel statistical methods; (iv) deliver training
on statistical methods; and (v) archive and publically share data. An external consultancy of internationally
recognized statisticians and quantitative methodologists will also provide ongoing consultation for the specific
types of analytic challenges anticipated (i.e., longitudinal structural equation modeling, missing data,
multilevel modeling of longitudinal data, psychometrics and latent variable modeling). Drawing on its panel of
expert statistical and methodological consultants and the data science team, Core C will also offer educational
services on innovative analytic and research methods to Program investigators, trainees, and the scientific
community (Aim 3). Lastly, in coordination with Core A, Core C will implement the P0...

## Key facts

- **NIH application ID:** 10181009
- **Project number:** 5P01HL040962-24
- **Recipient organization:** UNIVERSITY OF PITTSBURGH AT PITTSBURGH
- **Principal Investigator:** TIMOTHY D VERSTYNEN
- **Activity code:** P01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $434,998
- **Award type:** 5
- **Project period:** 1997-04-01 → 2023-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10181009

## Citation

> US National Institutes of Health, RePORTER application 10181009, Data Science & Management Core (5P01HL040962-24). Retrieved via AI Analytics 2026-05-27 from https://api.ai-analytics.org/grant/nih/10181009. Licensed CC0.

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