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Tu C Le

Showing results (1-10 of 39) with videos related to

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Molecular Informatics|October 27, 2016
Performance of Deep and Shallow Neural Networks, the Universal Approximation Theorem, Activity Cliffs, and QSARDavid A Winkler, Tu C Le
Chemmedchem|June 11, 2015
A Bright Future for Evolutionary Methods in Drug DesignTu C Le, David A Winkler
Molecular Informatics|November 9, 2017
Corrigendum: Performance of Deep and Shallow Neural Networks, the Universal Approximation Theorem Activity Cliffs, and QSARDavid A Winkler, Tu C Le
Chemical Reviews|May 13, 2016
Discovery and Optimization of Materials Using Evolutionary ApproachesTu C Le, David A Winkler
Journal of Chemical Information and Modeling|December 11, 2012
Capturing the crystal: prediction of enthalpy of sublimation, crystal lattice energy, and melting points of organic compoundsMaryam Salahinejad, Tu C Le, David A Winkler
Molecular Pharmaceutics|May 31, 2013
Aqueous solubility prediction: do crystal lattice interactions help?Maryam Salahinejad, Tu C Le, David A Winkler
Scientific Reports|January 24, 2019
Quantitative design rules for protein-resistant surface coatings using machine learningTu C Le, Matthew Penna, David A Winkler, et al.
Molecular Pharmaceutics|December 2, 2017
Correction to "Modeling the Influence of Fatty Acid Incorporation on Mesophase Formation in Amphiphilic Therapeutic Delivery Systems"Tu C Le, Nhiem Tran, Xavier Mulet, et al.
Molecular Pharmaceutics|January 30, 2016
Modeling the Influence of Fatty Acid Incorporation on Mesophase Formation in Amphiphilic Therapeutic Delivery SystemsTu C Le, Nhiem Tran, Xavier Mulet, et al.
Molecular Pharmaceutics|March 8, 2013
Predicting the complex phase behavior of self-assembling drug delivery nanoparticlesTu C Le, Xavier Mulet, Frank R Burden, et al.
Pageof 4

Showing results (1-10 of 39) with videos related to

Sort By:
Pageof 4
Molecular Informatics|October 27, 2016
Performance of Deep and Shallow Neural Networks, the Universal Approximation Theorem, Activity Cliffs, and QSARDavid A Winkler, Tu C Le
Chemmedchem|June 11, 2015
A Bright Future for Evolutionary Methods in Drug DesignTu C Le, David A Winkler
Molecular Informatics|November 9, 2017
Corrigendum: Performance of Deep and Shallow Neural Networks, the Universal Approximation Theorem Activity Cliffs, and QSARDavid A Winkler, Tu C Le
Chemical Reviews|May 13, 2016
Discovery and Optimization of Materials Using Evolutionary ApproachesTu C Le, David A Winkler
Journal of Chemical Information and Modeling|December 11, 2012
Capturing the crystal: prediction of enthalpy of sublimation, crystal lattice energy, and melting points of organic compoundsMaryam Salahinejad, Tu C Le, David A Winkler
Molecular Pharmaceutics|May 31, 2013
Aqueous solubility prediction: do crystal lattice interactions help?Maryam Salahinejad, Tu C Le, David A Winkler
Scientific Reports|January 24, 2019
Quantitative design rules for protein-resistant surface coatings using machine learningTu C Le, Matthew Penna, David A Winkler, et al.
Molecular Pharmaceutics|December 2, 2017
Correction to "Modeling the Influence of Fatty Acid Incorporation on Mesophase Formation in Amphiphilic Therapeutic Delivery Systems"Tu C Le, Nhiem Tran, Xavier Mulet, et al.
Molecular Pharmaceutics|January 30, 2016
Modeling the Influence of Fatty Acid Incorporation on Mesophase Formation in Amphiphilic Therapeutic Delivery SystemsTu C Le, Nhiem Tran, Xavier Mulet, et al.
Molecular Pharmaceutics|March 8, 2013
Predicting the complex phase behavior of self-assembling drug delivery nanoparticlesTu C Le, Xavier Mulet, Frank R Burden, et al.
Pageof 4