Most Ligand-Based Classification Benchmarks Reward Memorization Rather than Generalization von Wallach, Izhar, Heifets, Abraham

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A structure-based approach for mapping adverse drug reactions to the perturbation of underlying biological pathways von Wallach, Izhar, Jaitly, Navdeep, Lilien, Ryan

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Virtual Decoy Sets for Molecular Docking Benchmarks von Wallach, Izhar, Lilien, Ryan

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The protein–small-molecule database, a non-redundant structural resource for the analysis of protein-ligand binding von Wallach, Izhar, Lilien, Ryan

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Pharmacophore inference and its application to computational drug discovery von Wallach, Izhar

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AI is a viable alternative to high throughput screening: a 318-target study von Wallach, Izhar, Bernard, Denzil, Nguyen, Kong, Ho, Gregory, Morrison, Adrian, Stecula, Adrian, Rosnik, Andreana, O’Sullivan, Ann Marie, Davtyan, Aram, Samudio, Ben, Thomas, Bill, Worley, Brad, Butler, Brittany, Laggner, Christian, Thayer, Desiree, Moharreri, Ehsan, Friedland, Greg, Truong, Ha, van den Bedem, Henry, Ng, Ho Leung, Stafford, Kate, Sarangapani, Krishna, Giesler, Kyle, Ngo, Lien, Mysinger, Michael, Ahmed, Mostafa, Anthis, Nicholas J., Henriksen, Niel, Gniewek, Pawel, Eckert, Sam, de Oliveira, Saulo, Suterwala, Shabbir, PrasadPrasad, Srimukh Veccham Krishna, Shek, Stefani, Contreras, Stephanie, Hare, Stephanie, Palazzo, Teresa, O’Brien, Terrence E., Van Grack, Tessa, Williams, Tiffany, Chern, Ting-Rong, Kenyon, Victor, Lee, Andreia H., Cann, Andrew B., Bergman, Bastiaan, Anderson, Brandon M., Cox, Bryan D., Warrington, Jeffrey M., Sorenson, Jon M., Goldenberg, Joshua M., Young, Matthew A., DeHaan, Nicholas, Pemberton, Ryan P., Schroedl, Stefan, Abramyan, Tigran M., Gupta, Tushita, Mysore, Venkatesh, Presser, Adam G., Ferrando, Adolfo A., Andricopulo, Adriano D., Ghosh, Agnidipta, Ayachi, Aicha Gharbi, Mushtaq, Aisha, Shaqra, Ala M., Toh, Alan Kie Leong, Smrcka, Alan V., Ciccia, Alberto, de Oliveira, Aldo Sena, Sverzhinsky, Aleksandr, de Sousa, Alessandra Mara, Agoulnik, Alexander I., Kushnir, Alexander, Freiberg, Alexander N., Statsyuk, Alexander V., Gingras, Alexandre R., Degterev, Alexei, Tomilov, Alexey, Vrielink, Alice, Garaeva, Alisa A., Bryant-Friedrich, Amanda, Caflisch, Amedeo, Patel, Amit K., Rangarajan, Amith Vikram, Matheeussen, An, Battistoni, Andrea, Caporali, Andrea, Chini, Andrea, Ilari, Andrea, Mattevi, Andrea, Foote, Andrea Talbot, Trabocchi, Andrea, Stahl, Andreas, Herr, Andrew B., Berti, Andrew, Freywald, Andrew, Reidenbach, Andrew G., Lam, Andrew, Cuddihy, Andrew R., White, Andrew, Taglialatela, Angelo

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Predicting Multiple Ligand Binding Modes Using Self-Consistent Pharmacophore Hypotheses von Wallach, Izhar, Lilien, Ryan

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Author Correction: AI is a viable alternative to high throughput screening: a 318-target study von Wallach, Izhar, Bernard, Denzil, Nguyen, Kong, Ho, Gregory, Morrison, Adrian, Stecula, Adrian, Rosnik, Andreana, O’Sullivan, Ann Marie, Davtyan, Aram, Samudio, Ben, Thomas, Bill, Worley, Brad, Butler, Brittany, Laggner, Christian, Thayer, Desiree, Moharreri, Ehsan, Friedland, Greg, Truong, Ha, van den Bedem, Henry, Ng, Ho Leung, Stafford, Kate, Sarangapani, Krishna, Giesler, Kyle, Ngo, Lien, Mysinger, Michael, Ahmed, Mostafa, Anthis, Nicholas J., Henriksen, Niel, Gniewek, Pawel, Eckert, Sam, de Oliveira, Saulo, Suterwala, Shabbir, PrasadPrasad, Srimukh Veccham Krishna, Shek, Stefani, Contreras, Stephanie, Hare, Stephanie, Palazzo, Teresa, O’Brien, Terrence E., Van Grack, Tessa, Williams, Tiffany, Chern, Ting-Rong, Kenyon, Victor, Lee, Andreia H., Cann, Andrew B., Bergman, Bastiaan, Anderson, Brandon M., Cox, Bryan D., Warrington, Jeffrey M., Sorenson, Jon M., Goldenberg, Joshua M., Young, Matthew A., DeHaan, Nicholas, Pemberton, Ryan P., Schroedl, Stefan, Abramyan, Tigran M., Gupta, Tushita, Mysore, Venkatesh, Presser, Adam G., Ferrando, Adolfo A., Andricopulo, Adriano D., Ghosh, Agnidipta, Ayachi, Aicha Gharbi, Mushtaq, Aisha, Shaqra, Ala M., Toh, Alan Kie Leong, Smrcka, Alan V., Ciccia, Alberto, de Oliveira, Aldo Sena, Sverzhinsky, Aleksandr, de Sousa, Alessandra Mara, Agoulnik, Alexander I., Kushnir, Alexander, Freiberg, Alexander N., Statsyuk, Alexander V., Gingras, Alexandre R., Degterev, Alexei, Tomilov, Alexey, Vrielink, Alice, Garaeva, Alisa A., Bryant-Friedrich, Amanda, Caflisch, Amedeo, Patel, Amit K., Rangarajan, Amith Vikram, Matheeussen, An, Battistoni, Andrea, Caporali, Andrea, Chini, Andrea, Ilari, Andrea, Mattevi, Andrea, Foote, Andrea Talbot, Trabocchi, Andrea, Stahl, Andreas, Herr, Andrew B., Berti, Andrew, Freywald, Andrew, Reidenbach, Andrew G., Lam, Andrew, Cuddihy, Andrew R., White, Andrew, Taglialatela, Angelo

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AI is a viable alternative to high throughput screening: a 318-target study von Wallach, Izhar, Bernard, Denzil, Nguyen, Kong, Ho, Gregory, Morrison, Adrian, Stecula, Adrian, Rosnik, Andreana, O'Sullivan, Ann Marie, Davtyan, Aram, Samudio, Ben, Thomas, Bill, Worley, Brad, Butler, Brittany, Laggner, Christian, Thayer, Desiree, Moharreri, Ehsan, Friedland, Greg, Truong, Ha, van den Bedem, Henry, Ng, Ho Leung, Stafford, Kate, Sarangapani, Krishna, Giesler, Kyle, Ngo, Lien, Mysinger, Michael, Ahmed, Mostafa, Anthis, Nicholas J, Henriksen, Niel, Gniewek, Pawel, Eckert, Sam, de Oliveira, Saulo, Suterwala, Shabbir, PrasadPrasad, Srimukh Veccham Krishna, Shek, Stefani, Contreras, Stephanie, Hare, Stephanie, Palazzo, Teresa, O'Brien, Terrence E, Van Grack, Tessa, Williams, Tiffany, Chern, Ting-Rong, Kenyon, Victor, Lee, Andreia H, Cann, Andrew B, Bergman, Bastiaan, Anderson, Brandon M, Cox, Bryan D, Warrington, Jeffrey M, Sorenson, Jon M, Goldenberg, Joshua M, Young, Matthew A, DeHaan, Nicholas, Pemberton, Ryan P, Schroedl, Stefan, Abramyan, Tigran M, Gupta, Tushita, Mysore, Venkatesh, Presser, Adam G, Ferrando, Adolfo A, Andricopulo, Adriano D, Ghosh, Agnidipta, Ayachi, Aicha Gharbi, Mushtaq, Aisha, Shaqra, Ala M, Toh, Alan Kie Leong, Smrcka, Alan V, Ciccia, Alberto, de Oliveira, Aldo Sena, Sverzhinsky, Aleksandr, de Sousa, Alessandra Mara, Agoulnik, Alexander I, Kushnir, Alexander, Freiberg, Alexander N, Statsyuk, Alexander V, Gingras, Alexandre R, Degterev, Alexei, Tomilov, Alexey, Vrielink, Alice, Garaeva, Alisa A, Bryant-Friedrich, Amanda, Caflisch, Amedeo, Patel, Amit K, Rangarajan, Amith Vikram, Matheeussen, An, Battistoni, Andrea, Caporali, Andrea, Chini, Andrea, Ilari, Andrea, Mattevi, Andrea, Foote, Andrea Talbot, Trabocchi, Andrea, Stahl, Andreas, Herr, Andrew B, Berti, Andrew, Freywald, Andrew, Reidenbach, Andrew G, Lam, Andrew, Cuddihy, Andrew R, White, Andrew, Taglialatela, Angelo

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Quetiapine Excretion Into Human Breast Milk von Yazdani-Brojeni, Parvaneh, Tanoshima, Reo, Taguchi, Nobuko, Garcia-Bournissen, Facundo, Wallach, Izhar, Moretti, Myla E, Verjee, Zulfikarali, Ito, Shinya

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Prediction of sub-cavity binding preferences using an adaptive physicochemical structure representation von Wallach, Izhar, Lilien, Ryan H.

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Small-molecule targeting AMPA-mediated excitotoxicity has therapeutic effects in mouse models for multiple sclerosis von Zhai, Dongxu, Yan, Shuxin, Samsom, James, Wang, Le, Su, Ping, Jiang, Anlong, Zhang, Haorui, Jia, Zhengping, Wallach, Izhar, Heifets, Abraham, Zanato, Chiara, Tseng, Chih-Chung, Wong, Albert H C, Greig, Iain R, Liu, Fang

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Normalizing Molecular Docking Rankings using Virtually Generated Decoys von Wallach, Izhar, Jaitly, Navdeep, Nguyen, Kong, Schapira, Matthieu, Lilien, Ryan

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Population PK modelling and simulation based on fluoxetine and norfluoxetine concentrations in milk: a milk concentration‐based prediction model von Tanoshima, Reo, Bournissen, Facundo Garcia, Tanigawara, Yusuke, Kristensen, Judith H., Taddio, Anna, Ilett, Kenneth F., Begg, Evan J., Wallach, Izhar, Ito, Shinya

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Most Ligand-Based Classification Benchmarks Reward Memorization Rather than Generalization von Wallach, Izhar, Heifets, Abraham

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Systems and methods for correcting error in a first classifier by evaluating classifier output in parallel von Wallach, Izhar, Heifets, Abraham Samuel, Nguyen, Kong Thong

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SYSTEMS AND METHODS FOR SCREENING COMPOUNDS IN SILICO von SORENSON, Jon, MYSORE, Venkatesh, WALLACH, Izhar, GUPTA, Tushita, FRIEDLAND, Greg

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METHOD FOR APPLYING A CONVOLUTIONAL NETWORK TO SPATIAL DATA von HEIFETS, Abraham, Samuel, WALLACH, Izhar, DZAMBA, Michael

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Systems and methods for applying a convolutional network to spatial data von Wallach, Izhar, Heifets, Abraham Samuel, Dzamba, Michael

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SYSTEMS AND METHODS FOR VIRTUAL SCREENING AND CLASSIFYING CHEMICAL COMPOUNDS FOR TARGET POLYMER BINDING von HEIFETS, Abraham, Samuel, WALLACH, Izhar, NGUYEN, Kong

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