Toggle navigation
Home
Search
Services
Blog
Contact
About
Minority Predoctoral Fellowship Program - NIGMS
Eke, Agatha N.
Johns Hopkins University, Baltimore, MD, United States
Search 3 grants from Agatha Eke
Search grants from Johns Hopkins University
Share this grant:
:
:
Abstract
Funding
Institution
Related projects
Publications
Comments
Recent in Grantomics:
Your institution
vs. funders. Who wins?
Read more...
How should you pick the next fundable research topic?
Read more...
Recently viewed grants:
Informatics Platform for Mammalian Gene Regulation at Isoform-level
Molecular Profiling of Diabetes and its Complications
Core A: Behavior and Imaging Core
Antihyperlipidemic Effects of Oyster Mushrooms
Mechanisms of Mutagenesis by Chemical Carcinogens
Recently added grants:
Making the HIV-1 gp41 pocket amenable to small-molecule drug discovery
Frontiers in Addiction Research and Pregnancy
Cancer Research Career Enhancement and Related Activities
Microscopy & Cell Analysis Shared Resource
Cell - and Circuit - Specific Exploration of HIV Neurogenomics in Context of Opiate and Cocaine Abuse
Abstract
Funding Agency
Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Predoctoral Individual National Research Service Award (F31)
Project #
5F31GM016448-02
Application #
2170987
Study Section
Special Emphasis Panel (SRC)
Project Start
1995-10-01
Project End
Budget Start
1995-10-01
Budget End
1996-09-30
Support Year
2
Fiscal Year
1995
Total Cost
Indirect Cost
Institution
Name
Johns Hopkins University
Department
Public Health & Prev Medicine
Type
Schools of Public Health
DUNS #
045911138
City
Baltimore
State
MD
Country
United States
Zip Code
21218
Related projects
NIH 1996
F31 GM
Minority Predoctoral Fellowship Program - NIGMS
Eke, Agatha N. / Johns Hopkins University
NIH 1995
F31 GM
Minority Predoctoral Fellowship Program - NIGMS
Eke, Agatha N. / Johns Hopkins University
NIH 1994
F31 GM
Minority Predoctoral Fellowship Program - NIGMS
Eke, Agatha N. / Johns Hopkins University
Publications
Beck, Daniel; Foster, James A
(2015)
Machine learning classifiers provide insight into the relationship between microbial communities and bacterial vaginosis.
BioData Min 8:23
Comments
Be the first to comment on this grant