Project Grant DP2GM149556
Award Date
9/8/22
Completion Date
8/31/25
Dollars Obligated
$2.3M
Funding Federal Agency
Assistant Secretary for Financial Resources
Awarding Federal Agency
National Institute of General Medical Sciences
Federal Grant Program
93.859
Assistance Type
Project Grant
Place of Performance
Pasadena, CA 91125, USA
Similar Awards
This Project Grant award from the National Institutes of Health (NIH) Office of the Director under the Trans-NIH Research Support program (CFDA 93.310) is providing $290,325 to the University of Illinois to develop advanced deep learning methods for estimating cell-type resolution and spatially-resolved gene regulatory networks from spatial transcriptomics data. The objectives are to: 1) Create machine learning models that can integrate regulatory network components and distinguish cell types...
The National Institute of General Medical Sciences (NIGMS) awarded a $371,427 Project Grant under the Biomedical Research and Research Training program (CFDA 93.859) to Carnegie Mellon University. The goal of this 5-year project is to develop novel high-throughput machine learning approaches to study cell population-wide differences in subcellular object morphology, conformations, and organization using cryo-electron tomography (cryo-ET) data. The key products will include: 1) Domain...
This $1,737,000 Project Grant awarded by the National Institute of General Medical Sciences (NIGMS) under the Biomedical Research and Research Training program (CFDA 93.859) supports the development of innovative single-cell genomics technologies for joint analysis of regulatory dynamics and transcriptional states. Key objectives include: Developing multiomics tools to measure rates of epigenomic changes (DNA methylation, demethylation, oxidative damage, DNA repair) and relate these to...
This Project Grant award from the National Institute of General Medical Sciences (NIGMS) under the Biomedical Research and Research Training program (CFDA 93.859) provides $359,490 to the University of Florida to develop deep learning methods for integrating single-cell genomic data into genetic analysis. The key products and services to be delivered include: A novel deep learning model to predict gene expression from DNA sequences, enabling comprehensive characterization of cell-specific...
This National Science Foundation (NSF) Biological Sciences program Project Grant, with an award date of October 1, 2023 and total funding of $256,667.00, supports the development of advanced computational models to measure cellular traits in microscopy images. The goal is to create a universal deep-learning model that can readily quantify cell morphology in any microscopy image, with minimal training required. Specific objectives include developing methods for learning and extracting...
The National Institutes of Health (NIH) Office of the Director has awarded Carnegie Mellon University a $286,326 Project Grant under the Trans-NIH Research Support program (CFDA 93.310) to develop new machine learning methods for integrative analysis of spatial transcriptome datasets from NIH Common Fund programs. The key products and services to be delivered under this award include: Creating a scalable, platform-agnostic framework using pre-trained single-cell RNA-seq foundation models to...
This Project Grant award from the National Institute of General Medical Sciences (NIGMS) Biomedical Research and Research Training Program (CFDA 93.859) provides $363,384 to Duke University to develop a suite of computational tools to address key challenges in analyzing in situ spatial transcriptomics data. The project aims to: Develop a framework for optimized cell segmentation that integrates RNA spatial location information with imaging data, using the latest segmentation algorithms. The...
This Project Grant award from the National Institute of Environmental Health Sciences (NIEHS) under the Medical Library Assistance (CFDA 93.879) federal grant program provides $338,538 to The Regents of the University of California, San Francisco (UCSF) to develop a novel deep learning framework called DeepGene. The goal is to utilize this framework to synthesize disparate and large datasets of the mouse brain, including spatial transcriptomics, connectomics, proteomics, and functional data,...
The federal Project Grant award R01HG014004, in the amount of $550,810.00, was provided by the National Human Genome Research Institute (NHGRI) under the Human Genome Research program (CFDA 93.172). This grant will fund the development of an innovative AI-assisted laser capture microdissection (AI-LCM) approach for spatial transcriptomics, which aims to overcome limitations of existing spatial biology methods. The key products and services to be delivered under this grant include: Optimizing...
This two-year project grant from the National Science Foundation's Computer and Information Science and Engineering program aims to develop deep learning methods for high-resolution three-dimensional genome structure spatial reconstruction. With a total funding amount of $175,000, the award was issued on May 1, 2022 to the University of Colorado Colorado Springs to complete the project by April 30, 2024. The grantee will apply sophisticated and automated deep learning approaches to infer...