← Leaderboards
Billy Tsz Cheong Lau
Stanford University
$2,962,806
Attributed
$3,603,043
Total exposure
2
Grants
1
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 $1.1M · FY2020–25$2M$1.5M$1M$500K$0
'20
'21
'22
'23
'24
'25
Funding mix
By agency
NIH$3,603,043 · 2
By mechanism
R35$2,322,568 · 1
U01$1,280,475 · 1
Top collaborators
- Hanlee Ji2 shared
Most similar at Stanford University
Same institution · by research overlap
- Alain T Laederach$10,599,550
- Iain M Johnstone$10,221,358
- Hanlee Ji$24,780,644
- Karen G Hirsch$4,719,335
- Jonathan Elmer$7,634,354
Others in their field
Other Emerging Leaders on “Characteristics”
- Susan Abushakra · Alzheon, Inc.$47,265,244
- Susan M Landau · University Of California Berkeley$47,252,026
- Christopher Bee · Suny At Stony Brook$41,239,084
- John Hobbs · Suny At Stony Brook$41,239,084
- Phd, Stephen Schwartz · Fred Hutchinson Cancer Research Center$26,641,749
- Tharick Pascoal · University Of Pittsburgh At Pittsburgh$25,068,887
Research focus
CharacteristicsCohortSignal TransductionPreparationGenomicsCellsInnovationSamplingTechnologyData SetHuman BiologyExperimental StudyBioinformaticsEngineeringGenomeHuman DiseaseData IntegrationComplementary DnaComplexDropoutComputer FrameworkConsumptionAlgorithmsCellular Biology
Grant awards (7)
Single-molecule nanopore-based identification of methylome signatures in cfDNA for early colorectal cancer detection$640,695
U01 · FY2025 · CA
Single-molecule nanopore-based identification of methylome signatures in cfDNA for early colorectal cancer detection$639,780
U01 · FY2024 · CA
Omics information maximization in single-cell sequencing with hybrid molecular and computational approaches$471,022
R35 · FY2024 · HG · contact PI
Omics information maximization in single-cell sequencing with hybrid molecular and computational approaches$471,022
R35 · FY2023 · HG · contact PI
Omics information maximization in single-cell sequencing with hybrid molecular and computational approaches$471,022
R35 · FY2022 · HG · contact PI
Omics information maximization in single-cell sequencing with hybrid molecular and computational approaches$471,022
R35 · FY2021 · HG · contact PI
Omics information maximization in single-cell sequencing with hybrid molecular and computational approaches$438,480
R35 · FY2020 · HG · contact PI