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Ann Chesney Miller
Harvard Medical School
$2,653,443
Attributed
$30,000,379
Total exposure
6
Grants
0
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 $6.5M · FY2014–18$10M$7.5M$5M$2.5M$0
'14
'15
'16
'17
'18
Funding mix
By agency
NIH$30,000,379 · 6
By mechanism
U19$30,000,379 · 6
Top collaborators
- Darrell P Chandler31 shared
- Aedin C Culhane31 shared
- Molly Forrest Franke31 shared
- Jerome Timothy Galea31 shared
- Anne Goldfeld31 shared
- Louise Catherine Ivers31 shared
- Nira Pollock31 shared
- Eric Joseph Rubin31 shared
Most similar at Harvard Medical School
Same institution · by research overlap
- Jerome Timothy Galea$2,653,443
- Jeffrey R. Starke$2,653,443
- Aedin C Culhane$2,653,443
- Brian Meehan$107,284
- Gerhard Wagner$49,510,293
Others in their field
Top investigators on “Diagnosis”
- David Heimbrook · Leidos Biomedical Research, Inc.$590,717,255
- Bambra Strokes · Ppd Development Lp$526,656,217
- Leonard Freedman · Leidos Biomedical Research, Inc.$337,858,596
- Richard K. Wilson · Washington University$297,645,172
- Sharon A Nachman · Johns Hopkins University$212,395,175
- Carol Nesel · Westat$188,148,170
Research focus
DiagnosisInnovationDiagnosticMycobacterium TuberculosisDiagnostic TestsDrug ResistanceBaseDrug Resistance In TuberculosisPharmaceutical PreparationsPeruDesignResistanceMutationMutantUrineTuberculosisDetectionSamplingChildhoodChildCostTechnologyEarly DiagnosisCells
Grant awards (31)
Sequencing Core$2,595,356
U19 · FY2018 · AI
Genetic determinants of drug resistance in Mycobacteria tuberculosis$1,274,314
U19 · FY2018 · AI
Discovery and validation of drug resistance mutations$938,261
U19 · FY2018 · AI
Innovative Strategies to Improve Tuberculosis Diagnostics in Children$888,730
U19 · FY2018 · AI
Administrative Core$412,046
U19 · FY2018 · AI
Integrated system for Category C infectious disease diagnostics in resource-limi$403,448
U19 · FY2018 · AI
Integrated system for Category C infectious disease diagnostics in resource-limi$2,182,203
U19 · FY2017 · AI
Innovative Strategies to Improve Tuberculosis Diagnostics in Children$1,095,803
U19 · FY2017 · AI
Genetic determinants of drug resistance in Mycobacteria tuberculosis$913,253
U19 · FY2017 · AI
Discovery and validation of drug resistance mutations$734,112
U19 · FY2017 · AI
Administrative Core$616,131
U19 · FY2017 · AI
Sequencing Core$408,777
U19 · FY2017 · AI
Integrated system for Category C infectious disease diagnostics in resource-limi$2,528,705
U19 · FY2016 · AI
Innovative Strategies to Improve Tuberculosis Diagnostics in Children$992,134
U19 · FY2016 · AI
Discovery and validation of drug resistance mutations$750,894
U19 · FY2016 · AI
Genetic determinants of drug resistance in Mycobacteria tuberculosis$715,308
U19 · FY2016 · AI
Sequencing Core$421,675
U19 · FY2016 · AI
Administrative Core$410,524
U19 · FY2016 · AI
Genetic determinants of drug resistance in Mycobacteria tuberculosis$82,633
U19 · FY2016 · AI
Integrated system for Category C infectious disease diagnostics in resource-limi$2,500,809
U19 · FY2015 · AI
Innovative Strategies to Improve Tuberculosis Diagnostics in Children$932,090
U19 · FY2015 · AI
Discovery and validation of drug resistance mutations$774,241
U19 · FY2015 · AI
Sequencing Core$660,525
U19 · FY2015 · AI
Genetic determinants of drug resistance in Mycobacteria tuberculosis$500,331
U19 · FY2015 · AI
Administrative Core$311,434
U19 · FY2015 · AI
Integrated system for Category C infectious disease diagnostics in resource-limi$2,916,905
U19 · FY2014 · AI
Innovative Strategies to Improve Tuberculosis Diagnostics in Children$900,727
U19 · FY2014 · AI
Sequencing Core$822,385
U19 · FY2014 · AI
Discovery and validation of drug resistance mutations$554,926
U19 · FY2014 · AI
Genetic determinants of drug resistance in Mycobacteria tuberculosis$536,059
U19 · FY2014 · AI
Administrative Core$225,640
U19 · FY2014 · AI