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Funding

Clinical & Translational Science Institute / Funding / Pilot Awards / NBEM Awards

 

Novel Biostatistical and Epidemiologic Methods Awards

These awards support the development of novel biostatistical and epidemiologic methods that overcome analytic 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. 

Applications are now open! Submit initial abstracts by Monday, October 16 at 5 pm.

View the RFA

Apply

Solicitation and Review Process

Phase 1: Applicants submit one-page abstracts summarizing their proposals. A UR CTSI Review Committee composed of selected experts will evaluate, score and discuss all preliminary applications.

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.

CTSI Cost Sharing Information
CTSI Signoff Form 11/2021

View the 2023 RFA for the NBEM Pilot Award. 

Deadlines

The NBEM Funding Attestation must be submitted with the initial abstract and full proposal.

  • Monday, October 16, 2023, at 5:00 p.m. – Initial abstracts of proposals must be received. The submission system will reject proposals submitted after 5:00 pm.
  • Monday, November 20, 2023 – Applicants from whom full proposals will be solicited will be notified.
  • Monday, January 29, 2024, at 5:00 p.m. – Full proposals must be received. Proposals received after 5:00 pm will be rejected.
  • Monday, April 22, 2024 – Notifications of Award will be made. 
  • July 1, 2024 – The anticipated start date. 

Current Projects

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

Past Projects

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