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Igor V Tetko

Showing results (41-50 of 126) with videos related to

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Computational Biology and Chemistry|August 8, 2008
FunCat functional inference with belief propagation and feature integrationDimitrij Surmeli, Oliver Ratmann, Hans-Werner Mewes, et al.
Fungal Genetics and Biology : FG & B|January 16, 2007
Separation of sequences from host-pathogen interface using triplet nucleotide frequenciesJeppe Emmersen, Stephen Rudd, Hans-Werner Mewes, et al.
Journal of Pharmaceutical Sciences|August 8, 2008
Calculation of molecular lipophilicity: State-of-the-art and comparison of log P methods on more than 96,000 compoundsRaimund Mannhold, Gennadiy I Poda, Claude Ostermann, et al.
Journal of Chemical Information and Modeling|December 28, 2018
Comparative Study of Multitask Toxicity Modeling on a Broad Chemical SpaceSergey Sosnin, Dmitry Karlov, Igor V Tetko, et al.
Chemosphere|July 27, 2015
Identifying potential endocrine disruptors among industrial chemicals and their metabolites--development and evaluation of in silico toolsAleksandra Rybacka, Christina Rudén, Igor V Tetko, et al.
Nature Communications|November 5, 2020
State-of-the-art augmented NLP transformer models for direct and single-step retrosynthesisIgor V Tetko, Pavel Karpov, Ruud Van Deursen, et al.
Journal of Cheminformatics|January 12, 2021
GEN: highly efficient SMILES explorer using autodidactic generative examination networksRuud van Deursen, Peter Ertl, Igor V Tetko, et al.
Chemistry & Biodiversity|November 26, 2009
Large-scale evaluation of log P predictors: local corrections may compensate insufficient accuracy and need of experimentally testing every other compoundIgor V Tetko, Gennadiy I Poda, Claude Ostermann, et al.
Journal of Chemical Information and Modeling|December 20, 2023
When Yield Prediction Does Not Yield Prediction: An Overview of the Current ChallengesVarvara Voinarovska, Mikhail Kabeshov, Dmytro Dudenko, et al.
Journal of Molecular Graphics & Modelling|April 17, 2007
Volume learning algorithm significantly improved PLS model for predicting the estrogenic activity of xenoestrogensVasyl V Kovalishyn, Vladyslav Kholodovych, Igor V Tetko, et al.
Pageof 13

Showing results (41-50 of 126) with videos related to

Sort By:
Pageof 13
Computational Biology and Chemistry|August 8, 2008
FunCat functional inference with belief propagation and feature integrationDimitrij Surmeli, Oliver Ratmann, Hans-Werner Mewes, et al.
Fungal Genetics and Biology : FG & B|January 16, 2007
Separation of sequences from host-pathogen interface using triplet nucleotide frequenciesJeppe Emmersen, Stephen Rudd, Hans-Werner Mewes, et al.
Journal of Pharmaceutical Sciences|August 8, 2008
Calculation of molecular lipophilicity: State-of-the-art and comparison of log P methods on more than 96,000 compoundsRaimund Mannhold, Gennadiy I Poda, Claude Ostermann, et al.
Journal of Chemical Information and Modeling|December 28, 2018
Comparative Study of Multitask Toxicity Modeling on a Broad Chemical SpaceSergey Sosnin, Dmitry Karlov, Igor V Tetko, et al.
Chemosphere|July 27, 2015
Identifying potential endocrine disruptors among industrial chemicals and their metabolites--development and evaluation of in silico toolsAleksandra Rybacka, Christina Rudén, Igor V Tetko, et al.
Nature Communications|November 5, 2020
State-of-the-art augmented NLP transformer models for direct and single-step retrosynthesisIgor V Tetko, Pavel Karpov, Ruud Van Deursen, et al.
Journal of Cheminformatics|January 12, 2021
GEN: highly efficient SMILES explorer using autodidactic generative examination networksRuud van Deursen, Peter Ertl, Igor V Tetko, et al.
Chemistry & Biodiversity|November 26, 2009
Large-scale evaluation of log P predictors: local corrections may compensate insufficient accuracy and need of experimentally testing every other compoundIgor V Tetko, Gennadiy I Poda, Claude Ostermann, et al.
Journal of Chemical Information and Modeling|December 20, 2023
When Yield Prediction Does Not Yield Prediction: An Overview of the Current ChallengesVarvara Voinarovska, Mikhail Kabeshov, Dmytro Dudenko, et al.
Journal of Molecular Graphics & Modelling|April 17, 2007
Volume learning algorithm significantly improved PLS model for predicting the estrogenic activity of xenoestrogensVasyl V Kovalishyn, Vladyslav Kholodovych, Igor V Tetko, et al.
Pageof 13