Toward More Reliable 13C and 1H Chemical Shift Prediction: A Systematic Comparison of Neural-Network and Least-Squares Regression Based Approaches YD Smurnyy, KA Blinov, TS Churanova, ME Elyashberg, AJ Williams Journal of Chemical Information and Modeling 48 (1), 128-134, 2008 | 82 | 2008 |
Computer-assisted methods for molecular structure elucidation: realizing a spectroscopist's dream M Elyashberg, K Blinov, S Molodtsov, Y Smurnyy, AJ Williams, ... Journal of Cheminformatics 1, 1-26, 2009 | 75 | 2009 |
Development of a fast and accurate method of 13C NMR chemical shift prediction KA Blinov, YD Smurnyy, TS Churanova, ME Elyashberg, AJ Williams Chemometrics and Intelligent Laboratory Systems 97 (1), 91-97, 2009 | 57 | 2009 |
Empirical and DFT GIAO quantum‐mechanical methods of 13C chemical shifts prediction: competitors or collaborators? M Elyashberg, K Blinov, Y Smurnyy, T Churanova, A Williams Magnetic Resonance in Chemistry 48 (3), 219-229, 2010 | 48 | 2010 |
Performance Validation of Neural Network Based 13C NMR Prediction Using a Publicly Available Data Source KA Blinov, YD Smurnyy, ME Elyashberg, TS Churanova, M Kvasha, ... Journal of chemical information and modeling 48 (3), 550-555, 2008 | 40 | 2008 |
Fast search chemical structure in 90 million publicly available known compounds by NMR and MS T Churanova, K Blinov ABSTRACTS OF PAPERS OF THE AMERICAN CHEMICAL SOCIETY 255, 2018 | | 2018 |