← Leaderboards
Travis Steele Johnson
Ohio State University
$470,641
Attributed
$1,122,504
Total exposure
3
Grants
2
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 $428.5K · FY2019–24$500K$375K$250K$125K$0
'19
'20
'21
'22
'23
'24
Funding mix
By agency
NIH$1,122,504 · 3
By mechanism
R01$682,376 · 1
R21$393,892 · 1
F31$46,236 · 1
Most similar at Ohio State University
Same institution · by research overlap
- Joel H Saltz$14,758,457
- Laura Elske Maria Wisse$936,613
- Deliang Guo$11,121,635
- Jill A Rafael-Fortney$9,863,077
- Jay Louis Zweier$32,737,666
Others in their field
Other Emerging Leaders on “Cells”
- Douglas S. Hawkins · Children'S Hosp Of Philadelphia$155,695,588
- Gautam (george) Mitra · Leidos Biomedical Research, Inc.$53,523,213
- Evan Z Macosko · Broad Institute, Inc.$33,096,828
- James Dale Berry · Brigham And Women'S Hospital$30,122,905
- Hanjoon Ryu$28,519,898
- Eric C Palm · Florida State University$26,502,247
Research focus
CellsTumorTissuesSingle-Cell Rna SequencingImageHistologyTranscriptomicsGene ExpressionResolutionImage AnalysisMolecularMapsLearning AlgorithmResearch PersonnelSamplingHistological ImageAnticancer ResearchGlioblastomaField StudyNational Institute Of General Medical SciencesCell TypeMolecular ProfilingNeural Network SimulationMachine Learning
Grant awards (8)
DMS/NIGMS 1: Topological Study on Histological Images and Spatial Transcriptomics$199,468
R01 · FY2024 · GM
DMS/NIGMS 1: Topological Study on Histological Images and Spatial Transcriptomics$67,592
R01 · FY2024 · GM
DMS/NIGMS 1: Topological Study on Histological Images and Spatial Transcriptomics$200,260
R01 · FY2023 · GM
A deep-transfer-learning framework to transfer clinical information to single cells and spatial locations in cancer tissues$180,409
R21 · FY2023 · CA · contact PI
DMS/NIGMS 1: Topological Study on Histological Images and Spatial Transcriptomics$215,056
R01 · FY2022 · GM
A deep-transfer-learning framework to transfer clinical information to single cells and spatial locations in cancer tissues$213,483
R21 · FY2022 · CA · contact PI
Transfer learning approaches for integration of single cell RNA sequencing data from multiple sources$12,953
F31 · FY2020 · LM · contact PI
Transfer learning approaches for integration of single cell RNA sequencing data from multiple sources$33,283
F31 · FY2019 · LM · contact PI