Project Grant 2601546
- Federal Grant Award Summary The University of Wisconsin-Madison received a $327,547 Project Grant from the National Science Foundation's Division of Mathematical Sciences (CFDA 47.049 - Mathematical and Physical Sciences) awarded September 1, 2026, through August 31, 2029. This collaborative research project develops a mathematical framework and computational algorithms for scalable species tree estimation from whole-genome data using site pattern scoring schemes. The core deliverable...
- This National Science Foundation (NSF) Directorate for Mathematical and Physical Sciences Project Grant of $295,263 aims to improve the estimation of species trees from genomic datasets. The award, under the Mathematical and Physical Sciences program (CFDA 47.049), will fund the development of innovative mathematical, statistical, and computational techniques to analyze phylogenomic data without relying on gene tree estimation. This approach is intended to produce more reliable species tree...
- This National Science Foundation project grant of $638,016 awarded to Claremont McKenna College on May 1, 2022 under the Computer and Information Science and Engineering program (CFDA 47.070) will support the development of new algorithms and software tools to analyze phylogenetic tree reconciliations. Specifically, the award will fund research to design efficient algorithms for identifying best representative reconciliations of pairs of phylogenetic trees, such as those depicting hosts and...
- The National Science Foundation (NSF) Division of Mathematical Sciences awarded a $274,320 Project Grant to the University Enterprises Corporation at California State University, San Bernardino (CSUSB) to support the "PRIMES: PRACTICAL INFERENCE ALGORITHMS TO DETECT HYBRIDIZATION" project. Through this 2-year award, the principal investigator will develop algorithms to detect hybridization (the merging of distinct species to create a new one) and implement them in publicly available...
- This $2,963,428 Project Grant award from the National Science Foundation's Biological Sciences program (CFDA 47.074) aims to develop critical infrastructure and tools for interpreting genomic data. The project will create high-quality genome assembly workflows, comprehensive documentation, and interactive training materials to make these advanced genomic analysis capabilities accessible to a wide audience of biology researchers. This will enable downstream discoveries in areas such as...
- Federal Grant Award Summary The Division of Mathematical Sciences (DMS) within the National Science Foundation awarded a $500,000 Project Grant to Stanford University on August 1, 2025, under the Mathematical and Physical Sciences program (CFDA 47.049). This four-year research initiative, extending through July 31, 2029, develops enumerative combinatorics frameworks that characterize novel discrete mathematical structures underlying phylogenetic trees and networks. The research delivers...
- This collaborative research project grant of $749,739, awarded August 1, 2026, through the National Science Foundation's Division of Environmental Biology under the Biological Sciences program (CFDA 47.074), supports fundamental research examining the repeatability and diversity of evolutionary pathways in species interactions. The primary deliverable is a long-term laboratory evolution experiment conducted at the University of California, San Diego, investigating how ecological interactions...
- Federal Grant Award Summary The National Science Foundation's Division of Computing and Communication Foundations awarded UC Riverside a $600,000 Project Grant effective July 1, 2025, through June 30, 2028, under the Computer and Information Science and Engineering (CISE) program (CFDA 47.070). This award funds research to develop improved computational methods for de novo genome assembly using single-copy k-mers. The project addresses a critical challenge in computational biology where...
- This federal Project Grant award of $116,354, provided by the National Science Foundation's (NSF) Division of Mathematical Sciences under the Mathematical and Physical Sciences program (CFDA 47.049), supports collaborative research to develop a mathematical theory for the biological concept of modularity. The research aims to define modular structures in biological systems, such as gene regulatory networks underlying salamander limb regeneration and hormone regulation in plants, in a...
- This Project Grant from the National Science Foundation's Biological Sciences program (CFDA 47.074) provides $499,622 to North Carolina State University to develop computational models and analyze genomic data from over 60 species. The researchers will improve existing evolutionary modeling software to infer gene co-evolution networks from comparative genomics of more than a dozen independent polyploidy events. They will identify gene pairs where differences in copy number are evolutionarily...
This collaborative research project grant, awarded by the National Science Foundation's Division of Mathematical Sciences under the Mathematical and Physical Sciences program (CFDA 47.049), provides $299,846 in funding to UC San Diego for the period September 1, 2026 through August 31, 2029. The project develops mathematical frameworks and algorithms for scalable species tree estimation from whole-genome data, building upon the CASTER (site-based method) approach that uses quartet-based linear scoring schemes. Key deliverables include theoretical characterization of valid linear scoring methods under multiple evolutionary models, improved scoring algorithms, and extension of the methodology to additional biological settings including multispecies coalescent models, multi-copy genes, and substitution-rate heterogeneity. The project will produce open-source software tools for genome-scale evolutionary analysis and distribute these tools through software schools and training programs. Broader impacts include advancing biological discovery applications relevant to biotechnology, invasive species management, and disease outbreak analysis, while simultaneously contributing methodological innovations applicable to artificial intelligence and machine learning approaches for analyzing large heterogeneous datasets. The work will also support student training at the interface of mathematics, computer science, and biology, strengthening the Nation's scientific workforce in computational biology and bioinformatics.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $299.8k | 6/1/26 |