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Trends in Microbiology
|
June 18, 2017
Antimycobacterial Metabolism: Illuminating Mycobacterium tuberculosis Biology and Drug Discovery
Divya Awasthi, Joel S Freundlich
Pharmaceutical Research
|
May 7, 2011
Validating new tuberculosis computational models with public whole cell screening aerobic activity datasets
Sean Ekins, Joel S Freundlich
Methods in Molecular Biology (Clifton, N.J.)
|
April 10, 2013
Computational models for tuberculosis drug discovery
Sean Ekins, Joel S Freundlich
Inorganic Chemistry
|
December 4, 1996
Synthesis of Triamidoamine Complexes of Niobium
Joel S. Freundlich, Richard R. Schrock
F1000Research
|
February 10, 2015
A common feature pharmacophore for FDA-approved drugs inhibiting the Ebola virus
Sean Ekins, Joel S Freundlich, Megan Coffee
Journal of Chemical Information and Modeling
|
October 23, 2013
Fusing dual-event data sets for Mycobacterium tuberculosis machine learning models and their evaluation
Sean Ekins, Joel S Freundlich, Robert C Reynolds
Drug Discovery Today
|
July 5, 2014
Minding the gaps in tuberculosis research
Sean Ekins, Eric L Nuermberger, Joel S Freundlich
Journal of Chemical Information and Modeling
|
June 27, 2014
Are bigger data sets better for machine learning? Fusing single-point and dual-event dose response data for Mycobacterium tuberculosis
Sean Ekins, Joel S Freundlich, Robert C Reynolds
Nature Reviews. Microbiology
|
December 15, 2007
Drugs versus bugs: in pursuit of the persistent predator Mycobacterium tuberculosis
James C Sacchettini, Eric J Rubin, Joel S Freundlich
Pharmaceutical Research
|
August 31, 2013
Computational models for neglected diseases: gaps and opportunities
Elizabeth L Ponder, Joel S Freundlich, Malabika Sarker, et al.
Page
of 11
Search research articles
Search
Showing results (1-10 of 105) with videos related to
Sort By:
Page
of 11
Trends in Microbiology
|
June 18, 2017
Antimycobacterial Metabolism: Illuminating Mycobacterium tuberculosis Biology and Drug Discovery
Divya Awasthi, Joel S Freundlich
Pharmaceutical Research
|
May 7, 2011
Validating new tuberculosis computational models with public whole cell screening aerobic activity datasets
Sean Ekins, Joel S Freundlich
Methods in Molecular Biology (Clifton, N.J.)
|
April 10, 2013
Computational models for tuberculosis drug discovery
Sean Ekins, Joel S Freundlich
Inorganic Chemistry
|
December 4, 1996
Synthesis of Triamidoamine Complexes of Niobium
Joel S. Freundlich, Richard R. Schrock
F1000Research
|
February 10, 2015
A common feature pharmacophore for FDA-approved drugs inhibiting the Ebola virus
Sean Ekins, Joel S Freundlich, Megan Coffee
Journal of Chemical Information and Modeling
|
October 23, 2013
Fusing dual-event data sets for Mycobacterium tuberculosis machine learning models and their evaluation
Sean Ekins, Joel S Freundlich, Robert C Reynolds
Drug Discovery Today
|
July 5, 2014
Minding the gaps in tuberculosis research
Sean Ekins, Eric L Nuermberger, Joel S Freundlich
Journal of Chemical Information and Modeling
|
June 27, 2014
Are bigger data sets better for machine learning? Fusing single-point and dual-event dose response data for Mycobacterium tuberculosis
Sean Ekins, Joel S Freundlich, Robert C Reynolds
Nature Reviews. Microbiology
|
December 15, 2007
Drugs versus bugs: in pursuit of the persistent predator Mycobacterium tuberculosis
James C Sacchettini, Eric J Rubin, Joel S Freundlich
Pharmaceutical Research
|
August 31, 2013
Computational models for neglected diseases: gaps and opportunities
Elizabeth L Ponder, Joel S Freundlich, Malabika Sarker, et al.
Page
of 11