Project Grant 2437171
- 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...
- The National Science Foundation awarded Florida Atlantic University a $596,571 project grant under the Biological Sciences program (CFDA 47.074) to develop statistical tools for analyzing trait evolution across species from September 1, 2021 through August 31, 2024. As part of this award, FAU will create computational methods for learning about patterns of trait changes using phylogenetic and other comparative biological data to advance understanding of major problems in the biological sciences,...
- This $139,114 project grant from the National Science Foundation's Biological Sciences program (CFDA 47.074) will support the development of computational models to predict changes in biodiversity patterns over time at the University of Kansas Center for Research, Inc. Over the one-year period from May 2023 to April 2024, the awardee will synthesize decades of species distribution data and research to generate dynamic models incorporating factors like physiology and species interactions. A...
- This two-year, $276,000 National Science Foundation project grant funds statistical modeling and simulation research under the Biological Sciences program (CFDA 47.074). The grantee will develop a unified theoretical, empirical and computational framework to predict how ecological and evolutionary dynamics propagate in response to perturbations across scales over time. Using agent-based simulations of random and experimentally perturbed eco-evolutionary systems, the grantee will characterize...
- This $249,000 federal Project Grant award from the National Science Foundation (NSF) Biological Sciences (CFDA 47.074) program supports a phylogenetic investigation into the genetic basis of life history trait variation across eucalyptus trees. The project aims to leverage the diversity of wild eucalyptus species to gain insights into the genetic architecture underlying traits like overall size, growth, and reproduction in these economically important plants. The research will develop and...
- This Project Grant from the National Science Foundation Division of Environmental Biology provides $111,690 to Chatham University under the Biological Sciences program (CFDA 47.074) from May 1, 2022 to April 30, 2024. The award will support the development of a comprehensive learning platform synthesizing 25 years of research in permutational analytics for biological data analysis. Key products include an openly available full-length book and web-based tutorials demonstrating the...
- This Project Grant award from the National Science Foundation (NSF) Biological Sciences program (CFDA 47.074) provides $299,758 to the University of Washington to develop a novel method for estimating bacterial evolutionary histories. The key products and services to be delivered under this 2-year award include: Implementing and benchmarking a new mathematical approach for averaging gene-level phylogenies to obtain overall phylogenies for bacteria and archaea, even when not all genes are...
- The National Science Foundation (NSF) awarded a $299,868 project grant under the NSF Technology, Innovation, and Partnerships (CFDA 47.084) program to Iowa State University of Science and Technology. This 12-month grant, which began on June 15, 2024, aims to assess strategies for transitioning the open-source RevBayes phylogenetic software community into a self-sustaining and self-governing ecosystem. The project will investigate ways to improve the experiences of RevBayes users, contributors,...
- The National Science Foundation's (NSF) Biological Sciences (CFDA 47.074) Federal Grant Program has awarded $1,905,153.00 to Rice University to enable the development of "PhyNetPy" - a comprehensive, open-source Python library for phylogenetic network inference and analysis. This 4-year project (9/1/2025 - 8/31/2029) will create user-friendly tools, fundamental data structures, and essential components to allow developers and biologists to rapidly implement ideas and expand the...
- This $100,000 Project Grant award, funded by the National Science Foundation (NSF) Division of Environmental Biology under the Biological Sciences CFDA program, will support research to improve the representation of plants in ecosystem models. The key products and services to be delivered under this 3-year award include: Investigating methods to estimate plant traits using evolutionary histories to improve the parameterization of vegetation hydraulic traits in hydrologic and ecosystem models....
This $362,727 Project Grant was awarded on August 15, 2025 by the National Science Foundation's (NSF) Biological Sciences program (CFDA 47.074) to Towson University. The grant supports the development of new statistical models and computational methods to study the evolution of sequence traits in living organisms. The key products and services delivered under this award include: Creating advanced phylogenetic comparative methods that can model a large number of characteristics across an organism's developmental stages without significant increases in model complexity. This will enable researchers to analyze entire sequences of traits and explore new dimensions of biodiversity. Openly releasing all new models and algorithms developed as software packages for the R statistical programming language to facilitate broader use and adoption. Implementing a hands-on, research-based undergraduate course to train students in statistics, programming, data-driven research, and molecular substitution models - key skills for STEM careers. The new phylogenetic comparative methods aim to incorporate rate heterogeneity, estimate evolutionary trait correlations, and analyze diverse data types to advance the study of organismal phenomes. Extensive simulations and empirical analyses on frog ecomorphological traits and fossil developmental sequences will evaluate the efficiency and power of these innovative approaches.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $362.7k | 7/24/25 |