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Clinical & Translational Science Institute / Funding / Novel Biostatistical and Epidemiologic Methods Awards

Novel Biostatistical and Epidemiologic Methods Awards

These awards support the development of novel biostatistical and epidemiologic methods that overcome specifically identified limitations and enhance the validity, accuracy, scope, or speed of clinical or translational research. A maximum of $35,000 will be awarded for a one-year period. 

This funding opportunity is not currently open.

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Eligibility

All faculty members with a primary appointment at the University of Rochester are eligible to serve as principal investigators. Co-investigators may be from institutions other than the University of Rochester. Investigators who have received a Novel Biostatistical and Epidemiologic Methods award for two of the previous three years are ineligible to apply for the following year.  

Funding Amount

These awards provide up to $35,000 over one year.

Important Dates

The following dates apply to the most recent solicitation:

  • Abstracts due – October 16, 2023, at 5:00 p.m.
  • Notification of full proposal invitations – November 20, 2023
  • Full proposals​ due – January 29, 2024, at 5:00 p.m.
  • Notifications of award​ – April 22, 2024
  • Anticipated start date – July 1, 2024

Note: All animal and human subject protocols must be approved by NCATS, the NIH institute funding the CTSI, prior to the start date. No funds for research project costs may be released until all required human subjects and animal welfare approvals have been received.

Contact

General inquiries
Mary Little - mary_little@urmc.rochester.edu, (585) 275-0653

Scientific and peer review contacts

Robert Strawderman, ScD -robert_strawderman@urmc.rochester.edu
Edwin van Wijngaarden, PhD -edwin_van_wijngaarden@urmc.rochester.edu

Financial contact
Mary Lyons - mary_lyons@urmc.rochester.edu

Apply

Solicitation and Review Process

Phase 1: Applicants submit one-page abstracts summarizing their proposals. The abstracts are subjected to a preliminary review followed by a recommendation of which proposals should be solicited for full proposals.

Phase 2: A subset of applicants will be invited to submit full proposals. Proposals are reviewed by experts at another CTSA Program institution through an exchange program. Funding recommendations go to the UR CTSI Executive Team for final approval.

View the 2023 RFA for the NBEM Pilot Award. 

The NBEM Funding Attestation must be submitted with the initial abstract and full proposal.
CTSI Cost Sharing Information
CTSI Signoff Form 11/2021

Scholars and Projects

Current Projects 

Modeling neural responses to natural sounds using component-encoding models
Samuel Norman-Haignere, Ph.D.
Assistant Professor of Biostatistics and Computational Biology, Biomedical Engineering, and Neuroscience
Awarded in 2023

Past Projects

Differential abundance analysis of microbiota conditional on their functional difference
Michael Sohn, Ph.D.
Assistant Professor of Biostatistics and Computational Biology

Statistical methods to quantify imaged microglia
Matthew McCall, Ph.D. Biostat Bio
Associate Professor of Biostatistics

Inference on human populations from single cell transcriptional profiling
Andrew McDavid, Ph.D.
Assistant Professor of Biostatistics and Computational Biology

Machine learning based mediation analysis: Application in a study of birth weight
Ashkan Ertefaie, Ph.D.
Assistant Professor of Biostatistics and Computational Biology

Personalized medical image Analysis Based on Partial Differential Equations
Xing Qiu, Ph.D.
Associate Professor of Biostatistics and Computational Biology

Estimation of cell-type specific microRNA expression in complex tissue samples
Matthew McCall, Ph.D.
Assistant Professor of Biostatistics and Biomedical Genetics

Development of a Clinical Trial Simulation Tool for Huntington's Disease
Charles Venuto, PharmD
Assistant Professor of Neurology in the Center for Health and Technology

Development of qPCR methodology for clinical testing
Matthew McCall, Ph.D.
Assistant Professor of Biostatistics and Biomedical Genetics

Weighted Functional Gene Set Enrichment Analysis for Time-course Transcriptome Studies
Xing Qiu, Ph.D.
Associate Professor of Biostatistics and Computational Biology

Novel models for analyzing drinking outcomes: A pilot study comparing competing approaches
Hua He, Ph.D.
Assistant Professor, Biostatistics and Computational Biology

Detecting Intergene Association Changes in Microarray Data
Rui Hu, Ph.D.
Research Assistant Professor, Biostatistics and Computational Biology

Integrative Analysis of Pathways to SA and PPD in High Risk Families
Yinglin Xia, Ph.D., M.S.
Research Assistant Professor, Biostatistics and Computational Biology

Clustering Differentially Associated Genes
Rui Hu, Ph.D.
Research Assistant Professor of Biostatistics and Computational Biology
Co-Investgators: Sandhya Dwarkadas, PhD, Galina Glazko, PhD, Xing Qiu, PhD

Parameter estimation for nonlinear stochastic differential equation models from noisy longitudinal data in HIV dynamic research
Hongqi Xue, Ph.D.
Research Assistant Professor of Biostatistics and Computational Biology

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