Project Grant 2307571
- 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...
- The National Science Foundation Division of Information and Intelligent Systems awarded Indiana University a $113,029 Project Grant under the Computer and Information Science and Engineering program (CFDA 47.070). The grant supports research that will integrate deep learning and high-throughput experimentation to engineer proteins for non-native enzyme catalysis. Researchers will develop artificial intelligence models to interpret experimental data and guide iterative protein design. Two classes...
- This National Science Foundation (NSF) Project Grant, awarded under the Engineering program (CFDA 47.041), provides $357,033 to North Dakota State University (NDSU) from August 15, 2023 to July 31, 2026 to support research on protein manipulation and engineering using an electronic biochemical approach. The project aims to develop a single-molecule manipulation technique to study the dynamics of protein-protein interactions, which is critical for understanding the causes of diseases related to...
- This $500,000 federal Project Grant awarded by the National Science Foundation (NSF) under the Mathematical and Physical Sciences program (CFDA 47.049) supports research at Northwestern University to develop de novo designed proteins as mechano-responsive junctions in protein-polymer networks. The key objectives are to: (i) synthesize and computationally simulate de novo designed proteins and their respective protein-polymer networks, and (ii) develop techniques for mechanical characterization...
- This federal Project Grant award from the National Science Foundation's Biological Sciences program (CFDA 47.074) aims to advance protein function annotation by developing artificial intelligence (AI) and machine learning (ML) methods. The $298,251 award to Georgia Tech Research Corporation, a non-profit research organization, will fund research to improve the accuracy and coverage of protein function predictions and bridge the gap in function knowledge between understudied and...
- The National Science Foundation (NSF) awarded a $299,913 Project Grant under the Computer and Information Science and Engineering (CFDA 47.070) program to Rutgers, The State University in New Brunswick, NJ. This 2-year EAGER award titled "NAIRR PILOT: IMPRESS: INTEGRATED MACHINE-LEARNING FOR PROTEIN STRUCTURES AT SCALE" aims to harness artificial intelligence (AI) and high-performance computing (HPC) to revolutionize the design and validation of tailored proteins. The project will...
- 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 Project Grant award of $1,500,000 from the National Science Foundation's Mathematical and Physical Sciences program (CFDA 47.049) supports research to elucidate the design principles for de novo designed proteins as mechano-responsive junctions in protein-polymer networks. The key products and services to be delivered include: (1) Development of de novo designed proteins that can be readily transformed into junctions within polymer networks. (2) Investigation of the use of de novo...
- The National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) program awarded a $150,000 project grant to The University of Kentucky Research Foundation to develop deep-learning consistency models for simulating long-time scale protein dynamics. This 2-year project (8/1/2025 - 7/31/2027) aims to address the limitations of current molecular dynamics simulations in capturing the long-duration dynamics crucial for understanding protein folding and aggregation. By...
- This Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program, CFDA 47.070, provides $174,984 to Georgia Southern University Research & Service Foundation Inc. to develop a novel artificial intelligence (AI)-based computational framework. This framework aims to enhance the accuracy of modeling protein structures from medium-resolution cryo-electron microscopy (cryo-EM) images. By combining static quality information with...
This Project Grant award from the National Science Foundation (NSF) under the Computer and Information Science and Engineering program (CFDA 47.070) provides $101,368 to North Carolina Agricultural and Technical State University (NC A&T) to develop new computational methods for de novo protein sequencing and filling gaps in protein scaffolds. The key products and services to be delivered include: Through a two-phase approach, the researchers will first analyze top-down and bottom-up mass spectrometry data to construct protein scaffolds without a reference, using optimization, dynamic programming, and graph algorithms. In the second phase, they will apply deep learning techniques like convolutional neural networks, long short-term memory, and transformer models to complete the protein sequencing process. The project aims to create an open-source software framework that integrates these combinatorial and deep learning methods for improved protein scaffold filling. The research outputs are expected to significantly advance protein sequencing capabilities, benefiting fields like antibody research, and will be disseminated through publications, conferences, and educational initiatives at both the undergraduate and graduate levels.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $101.4k | 6/28/23 |