Project Grant 2515791
- This National Science Foundation project grant of $156,238 awarded on January 1, 2023 will fund research at Colorado State University to develop analytical tools combining heterogeneous genetic and molecular data sources to identify genetic modifiers of Parkinson's disease. Under the Mathematical and Physical Sciences program (CFDA 47.049), the researchers will use a hierarchical three-group mixture model to probabilistically model genes as null, deleterious, or beneficial based on genome-wide...
- This $138,428 project grant from the National Science Foundation's Computer and Information Science and Engineering program (CFDA 47.070) will support the development of computationally tractable structured hierarchical models to identify complex genetic associations hidden from current methods. The grantee, J. David Gladstone Institutes, will analyze genomic and clinical trait data using machine learning to build predictive models for individualized disease risk assessment and personalized...
- This National Science Foundation (NSF) Project Grant award under the Mathematical and Physical Sciences program (CFDA 47.049) provides $250,000 to The Trustees of the University of Pennsylvania to develop advanced statistical methods for integrating and analyzing large-scale data from multiple sources, such as electronic health records and genomics data. The project aims to devise new data-driven algorithms with theoretical optimality guarantees for transfer learning, as well as adversarially...
- This $794,457 federal Project Grant award from the National Science Foundation's (NSF) Biological Sciences program (CFDA 47.074) will support the development of new genetic analysis tools. The goal is to incorporate molecular and cellular biology knowledge, such as gene expression patterns and regulatory networks, directly into statistical models used to map genes, predict traits, and simulate changes in the genotype-to-phenotype relationships. The research will be conducted using simulated...
- This federal Project Grant award of $245,753.00 by the National Science Foundation's Social, Behavioral, and Economic Sciences program (CFDA 47.075) supports research into the translation of scientific research, specifically human genomic analysis, into a medical tool for newborn genomic screening. The project investigates the scientific research, biotechnology actors, and other interested parties driving this development, as well as its effects on patients, healthcare systems, and society....
- This Project Grant award of $520,720 from the National Science Foundation's (NSF) Biological Sciences program (CFDA 47.074) will support research to develop new tools for incorporating emerging models of genetics into genetic mapping, prediction, and simulation. The research, conducted by Colorado State University, aims to better integrate molecular and cellular biology knowledge into statistical models used to map genes, predict traits, and simulate changes in the genotype-to-phenotype...
- This Project Grant award from the National Science Foundation (CFDA 47.049 - Mathematical and Physical Sciences) in the amount of $197,007 is supporting collaborative research to develop new statistical theories and methodologies for tackling issues related to false discovery rate control in regression analysis. The research aims to provide novel statistical tools for analyzing complex data from diverse scientific domains such as brain imaging, genome-wide association studies, and atmospheric...
- This Project Grant award from the National Science Foundation (NSF) under the Mathematical and Physical Sciences Program (CFDA 47.049) is for a collaborative research project to develop methods to protect privacy and promote fairness in advanced genomic research using federated learning. The $250,000 award supports research to enable the integration of multi-cohort genomic and genetic datasets from different institutions, while addressing privacy and regulatory challenges associated with...
- This five-year, $997,720 Project Grant from the National Science Foundation's Computer and Information Science and Engineering program aims to develop new mathematical models and algorithms for genetic data analysis using deep learning techniques. Funded through the NSF's statutory mission to support basic research, the award will support research at Cornell University from July 2022 through June 2027. Specifically, the principal investigator will create novel deep generative models to replace...
- This $174,999 federal Project Grant award from the National Science Foundation's (NSF) Mathematical and Physical Sciences program supports a research project titled "Data Integration for Heterogeneous Data: A General Framework for Distribution Shift, Posterior Drift and Block Missing Data." The project aims to develop a new "Representation Retrieval (R2) Framework" to address key data integration challenges posed by heterogeneous datasets, including distribution...
This Project Grant award of $174,999 from the National Science Foundation (NSF) under the Mathematical and Physical Sciences program (CFDA 47.049) will support the development of new statistical tools to enhance the power and precision of discovering disease-associated genes. The project aims to uncover subtle genetic signals that might otherwise be missed by integrating diverse sources of genomic information and improving how prior knowledge and statistical evidence are combined. The innovations have the potential to transform the understanding and treatment of complex diseases, such as neurodegenerative disorders. The research will focus on two core challenges: (1) designing more effective weighting strategies for incorporating prior information when combining statistical significances, and (2) developing new methods to integrate discrete statistics within a general hypothesis testing framework. The project will implement and apply these approaches to harmonized whole genome sequencing datasets, with a focus on amyotrophic lateral sclerosis and related neurodegenerative diseases. The award period is from August 15, 2025 to July 31, 2028.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $175.0k | 8/5/25 |