Why is Tanimoto index an appropriate choice for fingerprint-based similarity calculations? D Bajusz, A Rácz, K Héberger Journal of cheminformatics 7, 1-13, 2015 | 1235 | 2015 |
Effect of dataset size and train/test split ratios in QSAR/QSPR multiclass classification A Rácz, D Bajusz, K Héberger Molecules 26 (4), 1111, 2021 | 213 | 2021 |
Consistency of QSAR models: Correct split of training and test sets, ranking of models and performance parameters A Rácz, D Bajusz, K Héberger SAR and QSAR in Environmental Research 26 (7-9), 683-700, 2015 | 107 | 2015 |
Multi-level comparison of machine learning classifiers and their performance metrics A Rácz, D Bajusz, K Héberger Molecules 24 (15), 2811, 2019 | 95 | 2019 |
Life beyond the Tanimoto coefficient: similarity measures for interaction fingerprints A Rácz, D Bajusz, K Héberger Journal of cheminformatics 10, 1-12, 2018 | 94 | 2018 |
Multivariate assessment of lipophilicity scales—computational and reversed phase thin-layer chromatographic indices F Andrić, D Bajusz, A Rácz, S Šegan, K Héberger Journal of Pharmaceutical and Biomedical Analysis 127, 81-93, 2016 | 65 | 2016 |
Chemical Data Formats, Fingerprints, and Other Molecular Descriptions for Database Analysis and Searching D Bajusz, A Rácz, K Héberger Comprehensive Medicinal Chemistry 3, 329-378, 2017 | 55* | 2017 |
Intercorrelation limits in molecular descriptor preselection for QSAR/QSPR A Rácz, D Bajusz, K Héberger Molecular informatics 38 (8-9), 1800154, 2019 | 48 | 2019 |
Extended similarity indices: the benefits of comparing more than two objects simultaneously. Part 1: Theory and characteristics† RA Miranda-Quintana, D Bajusz, A Rácz, K Héberger Journal of cheminformatics 13 (1), 32, 2021 | 45 | 2021 |
Is soft independent modeling of class analogies a reasonable choice for supervised pattern recognition? A Rácz, A Gere, D Bajusz, K Héberger RSC advances 8 (1), 10-21, 2018 | 40 | 2018 |
Modelling methods and cross-validation variants in QSAR: a multi-level analysis$ A Rácz, D Bajusz, K Héberger SAR and QSAR in Environmental Research 29 (9), 661-674, 2018 | 39 | 2018 |
Extended similarity indices: the benefits of comparing more than two objects simultaneously. Part 2: speed, consistency, diversity selection RA Miranda-Quintana, A Rácz, D Bajusz, K Héberger Journal of Cheminformatics 13 (1), 33, 2021 | 36 | 2021 |
Comparison of antioxidant capacity assays with chemometric methods A Rácz, N Papp, E Balogh, M Fodor, K Héberger Analytical Methods 7 (10), 4216-4224, 2015 | 34 | 2015 |
Reagent-free total protein quantification of intact extracellular vesicles by attenuated total reflection Fourier transform infrared (ATR-FTIR) spectroscopy V Szentirmai, A Wacha, C Németh, D Kitka, A Rácz, K Héberger, J Mihály, ... Analytical and bioanalytical chemistry 412, 4619-4628, 2020 | 33 | 2020 |
Machine learning models for classification tasks related to drug safety A Rácz, D Bajusz, RA Miranda-Quintana, K Héberger Molecular Diversity 25 (3), 1409-1424, 2021 | 32 | 2021 |
Quantitative determination of coenzyme Q10 from dietary supplements by FT-NIR spectroscopy and statistical analysis A Rácz, A Vass, K Héberger, M Fodor Analytical and Bioanalytical Chemistry 407, 2887-2898, 2015 | 32 | 2015 |
Comparison of descriptor-and fingerprint sets in machine learning models for ADME-Tox targets Á Orosz, K Héberger, A Rácz Frontiers in Chemistry 10, 852893, 2022 | 30 | 2022 |
Quantitative determination and classification of energy drinks using near-infrared spectroscopy A Rácz, K Héberger, M Fodor Analytical and Bioanalytical Chemistry, 2016 | 30 | 2016 |
Binary similarity measures for fingerprint analysis of qualitative metabolomic profiles A Rácz, F Andrić, D Bajusz, K Héberger Metabolomics 14, 1-9, 2018 | 24 | 2018 |
Molecular dynamics simulations and diversity selection by extended continuous similarity indices A Rácz, LM Mihalovits, D Bajusz, K Héberger, RA Miranda-Quintana Journal of Chemical Information and Modeling 62 (14), 3415-3425, 2022 | 23 | 2022 |