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Alexander P Clark
Cornell University
$99,062
Attributed
$99,062
Total exposure
1
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. They are the sole PI on all grants (the two match).
Funding over time
peak $39.6K · FY2020–22$50K$37.5K$25K$12.5K$0
'20
'21
'22
Funding mix
By agency
NIH$99,062 · 1
By mechanism
F31$99,062 · 1
Top collaborators
No co-investigators on record.
Most similar at Cornell University
Same institution · by research overlap
- Michael L Shuler$14,289,486
- Paula Elaine Cohen$17,058,525
- Robert S Weiss$9,017,992
- Marcus Smolka$8,381,271
- Anders Ryd$112,384,406
Others in their field
Other Emerging Leaders on “Adverse Effects”
- Susan Abushakra · Alzheon, Inc.$47,265,244
- Kristin Aillon · Midwest Research Institute$23,644,534
- Abraham Aizer Brody · New York University School Of Medicine$21,887,280
- Ellen Gould Chadwick · Harvard University D/B/A Harvard School Of Public Health$21,828,548
- Ionut Bebu · George Washington University$18,816,779
- Barbara Halina Braffett · George Washington University$18,816,779
Research focus
Adverse EffectsAction PotentialsAlgorithmsAnimalsAffectBaseBehaviorBenchmarkingBindingBlood PumpCardiacArrhythmiaCardiotoxicityCaviaCellsClinical TrialsClosure By ClampComplexComputer ModelsComputing MethodologiesCostData SetDesignDetection
Grant awards (3)
Predicting Drug Cardiotoxicity Targets Using iPSC-Derived Cardiomyocytes and Machine Learning$20,306
F31 · FY2022 · HL · contact PI
Predicting Drug Cardiotoxicity Targets Using iPSC-Derived Cardiomyocytes and Machine Learning$39,636
F31 · FY2021 · HL · contact PI
Predicting Drug Cardiotoxicity Targets Using iPSC-Derived Cardiomyocytes and Machine Learning$39,120
F31 · FY2020 · HL · contact PI