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Prediction of Synergism from Chemical-Genetic Interactions by Machine Learning.
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Shedding Light on Synergistic Chemical Genetic Connections with Machine Learning.
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6
Machine learning models identify molecules active against the Ebola virus .
F1000Res. 2015 Oct 20;4:1091. doi: 10.12688/f1000research.7217.3. eCollection 2015.
7
Open Source Bayesian Models. 3. Composite Models for Prediction of Binned Responses.
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Insights from the Structure of Mycobacterium tuberculosis Topoisomerase I with a Novel Protein Fold.
J Mol Biol. 2016 Jan 16;428(1):182-193. doi: 10.1016/j.jmb.2015.11.024. Epub 2015 Dec 3.
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The ELF Honest Data Broker: informatics enabling public-private collaboration in a precompetitive arena.
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10
Opportunities and Challenges for Natural Products as Novel Antituberculosis Agents.
Assay Drug Dev Technol. 2016 Jan-Feb;14(1):29-38. doi: 10.1089/adt.2015.673. Epub 2015 Nov 13.

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