Project Grant R01LM014674
- This federal Project Grant award of $1,968,575.00 from the National Institute of General Medical Sciences (NIGMS), under the Biomedical Research and Research Training program (CFDA 93.859), is focused on developing computational approaches and machine learning methods to predict DNA-binding specificities for transcription factor proteins and the functional effects of genetic variants within proteins. The overarching goal is to gain a predictive understanding of proteins, their interactions,...
- This Project Grant award of $894,785.00 from the National Science Foundation (NSF) Biological Sciences (CFDA 47.074) program will enable the development of an integrated experimental and computational platform to accelerate the discovery of protein-protein interactions (PPIs). The platform will combine an algorithmically optimized pooling scheme, immunopurification-mass spectrometry, and a novel sparse signal reconstruction algorithm to transform the PPI mapping problem into a more efficient...
- This federal Project Grant award from the National Institute of General Medical Sciences (NIGMS), under the Biomedical Research and Research Training program (CFDA 93.859), provides $431,800 to The University of Texas Southwestern Medical Center (UT Southwestern) to develop enhanced pipelines for proteome-wide protein-protein interaction (PPI) screening in humans. The project aims to leverage breakthroughs in protein structure prediction using deep learning and extensive genomic data to...
- This federal Project Grant award, valued at $287,488 and provided by the National Institute of General Medical Sciences (NIGMS) under the Biomedical Research and Research Training program (CFDA 93.859), supports a multi-year research initiative to deeply understand how proteins occupy conformational ensembles to enable biological functions. The overall goal is to develop strategies to computationally design new, functional protein ensembles from scratch, with a focus on engineering protein...
- The federal Project Grant award of $120,711 from the National Institute of General Medical Sciences (NIGMS) under CFDA 93.859 Biomedical Research and Research Training program aims to predict and validate druggable hyperreactive cysteines located within protein-protein interaction (PPI) interfaces. The project at the University of Texas Southwestern Medical Center seeks to develop an artificial intelligence-powered predictor for cysteine reactivity and identify reactive cysteines on human PPI...
- The National Institutes of Health (NIH) awarded a $1,476,000 Project Grant under the Trans-NIH Research Support program (CFDA 93.310) to The Trustees of Princeton University for a project titled "Algorithms and Software for Biomolecular Structure Determination at the Proteome Scale". The objective of this 3-year project, starting on September 9, 2025 and ending on August 31, 2028, is to develop novel artificial intelligence (AI) and machine learning (ML) methods to address critical...
- 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 $202,274 to develop an easy-to-use computer program for predicting the structure and degrading efficiency of proteolysis targeting chimeras (PROTACs). PROTACs are heterobifunctional molecules that induce the degradation of target proteins by recruiting them to E3 ubiquitin ligases. The awarded project aims to implement a...
- This federal Project Grant award from the National Science Foundation's Biological Sciences program (CFDA 47.074) in the amount of $100,000 will support collaborative research to develop deep learning-based "consistency models" that can simulate protein dynamics over long time scales. The goal is to overcome the limitations of current molecular dynamics simulation methods, which are constrained by the need for tiny time steps, in order to unlock new insights into protein behavior and...
- This federal Project Grant award from the National Institute of General Medical Sciences (NIGMS) under the Biomedical Research and Research Training program (CFDA 93.859) will fund a $540,000 research project at Northwestern University to measure the global folding stability and folding energy landscapes for 3 million protein sequences. The project aims to create a large dataset quantifying these properties, which have historically been challenging to investigate at scale. This data will empower...
- This $248,508 National Science Foundation project grant supports the development of computational tools and a database for modeling protein-protein and protein-nucleic acid interactions involving intrinsically disordered regions. Funded under the Biological Sciences program (CFDA 47.074), key products include high-accuracy prediction of binding regions within disordered sequences using multi-task deep learning models; identification of partner molecules for these regions; and structure...
This Project Grant award for $1,440,905, awarded on September 1, 2025 by the National Institute of Environmental Health Sciences, funds research to develop improved computational methods for predicting protein-protein interactions (PPIs). The project aims to create complementary approaches that can accurately predict both stable and transient PPIs, including those involving peptide-binding domains and post-translational modifications - areas that are challenging for existing PPI prediction tools like AlphaFold. The research is being conducted by the Trustees of Columbia University in the City of New York, leveraging the university's expertise in molecular machine learning and high-throughput PPI characterization. The work is supported under the Medical Library Assistance federal grant program (CFDA 93.879), which focuses on advancing biomedical informatics and data science to enhance healthcare knowledge and patient outcomes.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $1.4m | 9/1/25 |