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Dong Xu
University Of Missouri-Columbia
$6,081,005
Attributed
$6,081,005
Total exposure
5
Grants
5
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. They are the sole PI on all grants (the two match).
Funding over time
peak $612.9K · FY2006–25$1M$750K$500K$250K$0
'06
'07
'08
'09
'10
'11
'12
'13
'14
'15
'16
'17
'18
'19
'20
'21
'22
'23
'24
'25
Funding mix
By agency
NIH$6,081,005 · 5
By mechanism
R35$3,377,665 · 1
R01$1,384,673 · 1
R21$659,881 · 2
R33$658,786 · 1
Top collaborators
No co-investigators on record.
Most similar at University Of Missouri-Columbia
Same institution · by research overlap
- Xiaoqin Zou$6,077,987
- Jianlin Cheng$5,083,467
Others in their field
Top investigators on “Proteins”
- David Heimbrook · Leidos Biomedical Research, Inc.$354,061,551
- Randall J Bateman · Washington University$187,292,085
- Paul S. Aisen · Cognition Therapeutics, Inc.$175,382,342
- Reisa A. Sperling · Banner Health$145,046,481
- Barton F Haynes · Duke University$136,029,850
- Joseph L Goldstein · University Of Texas Sw Med Ctr/Dallas$102,433,280
Research focus
ProteinsBioinformaticsProtein Structure PredictionAmino Acid SequenceCommunitiesMutationResearch PersonnelProtein StructureBaseDeep LearningComputing MethodologiesOnline ResourceEvaluationBase SequenceLabelDesignMethodologyStructureComputational AlgorithmDatabasesAlgorithmsData AnalysesBiologyLight
Grant awards (21)
Multi-view self-supervised deep learning for biological sequences and beyond$391,250
R35 · FY2025 · GM · contact PI
Multi-view self-supervised deep learning for biological sequences and beyond$391,250
R35 · FY2024 · GM · contact PI
Multi-view self-supervised deep learning for biological sequences and beyond$391,250
R35 · FY2023 · GM · contact PI
Interpretable and extendable deep learning model for biological sequence analysis and prediction$456,433
R35 · FY2022 · GM · contact PI
Interpretable and extendable deep learning model for biological sequence analysis and prediction$378,183
R35 · FY2021 · GM · contact PI
Interpretable and extendable deep learning model for biological sequence analysis and prediction$234,750
R35 · FY2021 · GM · contact PI
Interpretable and extendable deep learning model for biological sequence analysis and prediction$378,183
R35 · FY2020 · GM · contact PI
Interpretable and extendable deep learning model for biological sequence analysis and prediction$378,183
R35 · FY2019 · GM · contact PI
Deep learning for protein subcellular/sub-organelle localizations and localization motifs$205,330
R21 · FY2019 · LM · contact PI
Interpretable and extendable deep learning model for biological sequence analysis and prediction$378,183
R35 · FY2018 · GM · contact PI
Deep learning for protein subcellular/sub-organelle localizations and localization motifs$174,375
R21 · FY2018 · LM · contact PI
Development of MUFOLD for Building High-Accuracy Protein Structure Models$278,351
R01 · FY2016 · GM · contact PI
Development of MUFOLD for Building High-Accuracy Protein Structure Models$278,628
R01 · FY2015 · GM · contact PI
Development of MUFOLD for Building High-Accuracy Protein Structure Models$278,896
R01 · FY2014 · GM · contact PI
Development of MUFOLD for Building High-Accuracy Protein Structure Models$269,387
R01 · FY2013 · GM · contact PI
Development of MUFOLD for Building High-Accuracy Protein Structure Models$279,411
R01 · FY2012 · GM · contact PI
New Scoring, Assembly and Evaulation Techiniques for Protein Structure Prediction$219,712
R33 · FY2010 · GM · contact PI
New Scoring, Assembly and Evaulation Techiniques for Protein Structure Prediction$220,339
R33 · FY2009 · GM · contact PI
New Scoring, Assembly and Evaulation Techiniques for Protein Structure Prediction$218,735
R33 · FY2008 · GM · contact PI
New Scoring, Assembly and Evaulation Techiniques for Protein Structure Prediction$137,920
R21 · FY2007 · GM · contact PI
New Scoring, Assembly and Evaulation Techiniques for Protein Structure Prediction$142,256
R21 · FY2006 · GM · contact PI