Project Grant R35GM152245
Award Date
5/1/24
Completion Date
3/31/29
Dollars Obligated
$733K
Federal Agency
National Institute of General Medical Sciences
Federal Grant Program
93.859
Assistance Type
Project Grant
Place of Performance
Atlanta, GA 30332, USA
Similar Awards
This Project Grant award from the National Cancer Institute (CFDA 93.394 - Cancer Detection and Diagnosis Research) totaling $710,656 provides funding to Loma Linda University to develop and validate a multi-stage, multi-modal "PROSPECT" score to risk-stratify oral premalignant lesions (OPL) and predict progression to oral cavity squamous cell carcinoma (OSCC). The project aims to train deep learning-based digital pathology models using cytology and histology data to predict OPL...
This $151,956 Project Grant award from the National Human Genome Research Institute (CFDA 93.172 - Human Genome Research) supports the "PATHFINDER: FINDING THE GENOMIC AND CLINICAL PATHWAYS UNDERLYING HETEROGENEITY IN COMPLEX DISEASE" research program at the Icahn School of Medicine at Mount Sinai. The goal of this research is to develop novel strategies to identify and understand the underlying mechanisms contributing to heterogeneity in complex diseases like schizophrenia,...
This $619,057 Project Grant award from the National Institute of Environmental Health Sciences (NIEHS) under the Medical Library Assistance (CFDA 93.879) program supports the development of statistical and machine learning methods to address the challenge of disease under-diagnosis using electronic health record (EHR) data. The key products and services to be delivered through this 5-year project include: Risk-based approaches to identify patients in EHRs who may be under-diagnosed for...
This Project Grant award, valued at $802,034 and funded by the National Institute on Aging's Aging Research program (CFDA 93.866), aims to develop a comprehensive "multimodal, multiscale and multistage systems biology (M3SB) infrastructure" to advance precision medicine for Alzheimer's disease (AD) and longevity research. The key objectives are to: 1) conduct multi-omics analyses to identify bioage-modifying targets and repurposable medicines for AD and related dementias; 2) build...
This Project Grant award for $432,304 from the National Cancer Institute (NCI) under the Cancer Cause and Prevention Research program (CFDA 93.393) aims to develop novel data integration methods to enhance cancer risk predictions for underrepresented minority populations, particularly Black and Hispanic individuals. The key products and services to be delivered include: 1) a transfer learning method to leverage external study data while accommodating various data sharing arrangements, 2) a...
This $2.757 million three-year Project Grant from the National Institutes of Health's Trans-NIH Research Support program will develop a computational framework for analyzing spatially-resolved transcriptomic datasets. The Broad Institute will integrate machine learning techniques such as representation learning, causal inference, image inpainting, and optimal transport to identify biological mechanisms underlying spatial processes in tissue contexts. Specifically, the framework will discern...
This $244,228 Project Grant award from the National Cancer Institute (NCI) under the Cancer Detection and Diagnosis Research program (CFDA 93.394) supports a research initiative to develop a functional proteomics approach for accurately mapping lung cancer patient tumors to preclinical models. The key products and services to be delivered include: Expanding the proteomic profiling of lung cancer patient-derived xenograft (PDX) models using a reverse-phase protein array (RPPA) platform that has...
This Project Grant award from the National Human Genome Research Institute (NHGRI), under the Human Genome Research federal grant program (CFDA 93.172), will provide $1,100,866 to the Icahn School of Medicine at Mount Sinai to develop new deep learning methods to predict disease risk for individuals harboring rare monogenic risk alleles. The goal is to refine the accuracy of genetic diagnostics and increase the clinical usefulness of genetic information by integrating non-genetic factors with...
This $255,994 Project Grant from the National Science Foundation's Engineering program (CFDA 47.041) will fund Sygnamap Inc. to develop a computational platform using spatial omics data to infer putative causative pathways of kidney disease. The platform will leverage mass spectrometry imaging and artificial intelligence/machine learning approaches to correlate and optimize the localization of molecules with pathologic features. This will identify key biochemical pathways that drive disease...
This $627,833 Project Grant award from the National Cancer Institute's Cancer Biology Research Program (CFDA 93.396) aims to develop an informatics platform that integrates molecular and pathological data from various lung cancer preclinical models and patient tumors. The key products and services to be delivered include: Harmonizing molecular profiling datasets from multiple lung cancer preclinical models and implementing statistical methods for cross-study validation and quality control....