← Leaderboards
Frederick Albert Matsen
Fred Hutchinson Cancer Center
$9,837,173
Attributed
$10,597,544
Total exposure
4
Grants
3
Lead (contact PI)
Attributed= this PI's even-split share of every grant they're on (the fair, additive number). Exposure = full size of all those grants.
Funding over time
peak $1.5M · FY2010–25$2M$1.5M$1M$500K$0
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Funding mix
By agency
NIH$10,597,544 · 4
By mechanism
R01$10,597,544 · 4
Top collaborators
- David Neal Fredricks3 shared
Most similar at Fred Hutchinson Cancer Center
Same institution · by research overlap
- Daniel Blanco-Melo$1,551,984
- Jesse D Bloom$13,760,302
Others in their field
Top investigators on “Collection”
- Sonia M Thomas · Research Triangle Institute$700,865,642
- Jeffrey P Krischer · University Of South Florida$574,712,442
- Tracy L Nolen · Research Triangle Institute$474,487,152
- David R. Weir · University Of Michigan At Ann Arbor$414,261,438
- David Heimbrook · Leidos Biomedical Research, Inc.$349,689,844
- Marian Ewell · The Emmes Company, Llc$276,352,498
Research focus
CollectionAlgorithmsSamplingStatistical ModelsPathogenComplexTechnologyUncertaintyTreesOpen SourceResearch PersonnelPhylogenetic AnalysisUpdateFoundationsProceduresModificationData SetLearningMachine LearningTrainingImmune SystemImmunoglobulin Somatic HypermutationImmuneAntibodies
Grant awards (20)
Fast and flexible Bayesian phylogenetics via modern machine learning$744,770
R01 · FY2025 · AI · contact PI
Fast and flexible Bayesian phylogenetics via modern machine learning$744,770
R01 · FY2024 · AI · contact PI
Blending deep learning with probabilistic mechanistic models to predict and understand the evolution and function of adaptive immune receptors$689,648
R01 · FY2024 · AI · contact PI
Fast and flexible Bayesian phylogenetics via modern machine learning$744,770
R01 · FY2023 · AI · contact PI
Fast and flexible Bayesian phylogenetics via modern machine learning$744,770
R01 · FY2022 · AI · contact PI
Blending deep learning with probabilistic mechanistic models to predict and understand the evolution and function of adaptive immune receptors$689,648
R01 · FY2022 · AI · contact PI
Blending deep learning with probabilistic mechanistic models to predict and understand the evolution and function of adaptive immune receptors$689,647
R01 · FY2021 · AI · contact PI
Fast and flexible Bayesian phylogenetics via modern machine learning$476,064
R01 · FY2021 · AI · contact PI
Fast and flexible Bayesian phylogenetics via modern machine learning$321,306
R01 · FY2021 · AI · contact PI
Blending deep learning with probabilistic mechanistic models to predict and understand the evolution and function of adaptive immune receptors$1
R01 · FY2021 · AI · contact PI
Blending deep learning with probabilistic mechanistic models to predict and understand the evolution and function of adaptive immune receptors$710,049
R01 · FY2020 · AI · contact PI
Blending deep learning with probabilistic mechanistic models to predict and understand the evolution and function of adaptive immune receptors$632,498
R01 · FY2019 · AI · contact PI
Leveraging deep sequencing data to understand antibody maturation$376,788
R01 · FY2018 · GM · contact PI
Leveraging deep sequencing data to understand antibody maturation$376,788
R01 · FY2017 · GM · contact PI
Leveraging deep sequencing data to understand antibody maturation$376,788
R01 · FY2016 · GM · contact PI
Leveraing deep sequencing data to understand antibody maturation$378,709
R01 · FY2015 · GM · contact PI
Leveraing deep sequencing data to understand antibody maturation$379,787
R01 · FY2014 · GM · contact PI
Novel Computational Tools for Studying the Human Microbiome$491,177
R01 · FY2012 · HG
Novel Computational Tools for Studying the Human Microbiome$495,844
R01 · FY2011 · HG
Novel Computational Tools for Studying the Human Microbiome$533,722
R01 · FY2010 · HG