Project Grant 2310113

Award Date 8/1/23
Completion Date 7/31/26
Dollars Obligated $600K
Federal Grant Program
47.070
Assistance Type
Project Grant
Place of Performance
Fairfax, VA, USA
Similar Awards
This Project Grant, awarded by the National Science Foundation Division of Information and Intelligent Systems, provides $599,871 to Emory University from August 1, 2023 to July 31, 2026. The funding supports collaborative research at the intersection of machine learning, bioinformatics, and molecular biology. The project aims to advance algorithmic research using principled protein language models (PLMs) to gain deeper insight into the structural, functional, and evolutionary organization of...
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) Computer and Information Science and Engineering (CISE) Federal Grant Award (CFDA 47.070) provides $150,000 in funding to the University of Missouri System to develop deep-learning based "consistency models" that can simulate the long-time dynamics of protein structures more efficiently than current molecular dynamics (MD) simulation methods. The project aims to overcome the limitations of MD simulations in capturing millisecond-scale protein...
This Project Grant award from the National Science Foundation (NSF) Division of Information and Intelligent Systems (CFDA #47.070 - Computer and Information Science and Engineering) provides $599,939 to Texas A&M Engineering Experiment Station (Tees) to develop novel 3D graph neural network algorithms and architectures. The key objectives are to (1) create 3D graph neural networks that can efficiently and accurately capture the geometric properties of small molecules and proteins to generate...
This National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) Federal Grant Award (CFDA 47.070) provides $150,000 to The University of Kentucky Research Foundation to develop deep learning-based "consistency models" to simulate the long-time scale dynamics of protein structures. The goal is to overcome the limitations of traditional molecular dynamics simulations in capturing the complex, millisecond-scale behavior of proteins, which is crucial for...
This Project Grant award from the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CFDA 47.070) program provides $389,494 to Northeastern University to develop new probabilistic programming languages (PPLs) that bridge the gap between high-level ergonomic languages and low-level tractable models. The key objectives are to: (1) create new high-level ergonomic PPLs that compile to low-level tractable probabilistic models; (2) develop new compilation...
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...
The federal Project Grant award, valued at $697,510.00 and funded by the National Science Foundation (NSF) Biological Sciences (CFDA 47.074) program, aims to improve, validate, and interpret amino acid substitution models for protein evolution. The research will enhance understanding of how substitutions of amino acids in proteins impact their form and function, which is critical for reconstructing the evolutionary history of proteins and advancing phylogenetic inference. The project, with a...
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...
This three-year $800,000 project grant from the National Science Foundation's Computer and Information Science and Engineering program aims to advance understanding of large language models through mathematical and conceptual analysis. The Trustees of Princeton University will receive funding to develop simplified generative text models, analyze how language models are trained on such generated texts, examine why learned models can perform downstream tasks, and design new adaptation methods with...

This Project Grant award from the National Science Foundation's (NSF) Division of Information and Intelligent Systems (CFDA 47.070 - Computer and Information Science and Engineering) provides $599,948 to George Mason University, doing business as Mason, to advance algorithmic research at the intersection of information integration and informatics using principled protein language models (PLMs) as computational vehicles.

The key objectives of this 3-year project are to: (1) encode prior biological knowledge in PLMs for joint and resource-aware learning in composite spaces, (2) reveal fundamental properties and organize the learned representation space to inform and connect what is captured with properties of interest, and (3) enable PLMs to capture diverse contexts for deeper exploration of the structural, functional, and evolutionary organization across protein space. This interdisciplinary research contributes to the fields of machine learning, bioinformatics, and molecular biology, and provides training opportunities for underrepresented students.

Generated 4/30/24, 2:14 PM