| Correction: Genotoxicity of metal oxide nanomaterials: review of recent data and discussion of possible mechanisms N Golbamaki, B Rasulev, A Cassano, RLM Robinson, E Benfenati, ... Nanoscale 7 (14), 6388-6388, 2015 | 210* | 2015 |
| Genotoxicity of metal oxide nanomaterials: review of recent data and discussion of possible mechanisms N Golbamaki, B Rasulev, A Cassano, RLM Robinson, E Benfenati, ... Nanoscale 7 (6), 2154-2198, 2015 | 210 | 2015 |
| Interpreting random forest classification models using a feature contribution method A Palczewska, J Palczewski, RM Robinson, D Neagu Integration of Reusable Systems, 193-218, 2014 | 179 | 2014 |
| The challenges involved in modeling toxicity data in silico: a review MP Gleeson, S Modi, A Bender, R L Marchese Robinson, J Kirchmair, ... Current pharmaceutical design 18 (9), 1266-1291, 2012 | 110 | 2012 |
| Comparison of the Predictive Performance and Interpretability of Random Forest and Linear Models on Benchmark Datasets RL Marchese Robinson, A Palczewska, J Palczewski, N Kidley Journal of Chemical Information and Modeling, 2017 | 109 | 2017 |
| How should the completeness and quality of curated nanomaterial data be evaluated? RLM Robinson, I Lynch, W Peijnenburg, J Rumble, F Klaessig, ... Nanoscale 8 (19), 9919-9943, 2016 | 106 | 2016 |
| Interpreting random forest models using a feature contribution method A Palczewska, J Palczewski, RM Robinson, D Neagu 2013 IEEE 14th International Conference on Information Reuse & Integration …, 2013 | 89 | 2013 |
| Hierarchical virtual screening for the discovery of new molecular scaffolds in antibacterial hit identification PJ Ballester, M Mangold, NI Howard, RLM Robinson, C Abell, ... Journal of The Royal Society Interface 9 (77), 3196-3207, 2012 | 83 | 2012 |
| Molecular fingerprint-derived similarity measures for toxicological read-across: Recommendations for optimal use CL Mellor, RLM Robinson, R Benigni, D Ebbrell, SJ Enoch, JW Firman, ... Regulatory Toxicology and Pharmacology 101, 121-134, 2019 | 72 | 2019 |
| Integration among databases and data sets to support productive nanotechnology: Challenges and recommendations NanoImpact, 2017 | 72* | 2017 |
| Development and comparison of hERG blocker classifiers: Assessment on different datasets yields markedly different results RL Marchese Robinson, RC Glen, JBO Mitchell Molecular Informatics 30 (5), 443-458, 2011 | 47 | 2011 |
| Perspectives from the NanoSafety Modelling Cluster on the validation criteria for (Q)SAR models used in nanotechnology T Puzyn, N Jeliazkova, H Sarimveis, RL Marchese Robinson, V Lobaskin, ... Food and Chemical Toxicology, 2017 | 35 | 2017 |
| Comparing the CORAL and Random Forest Approaches for Modelling the In Vitro Cytotoxicity of Silica Nanomaterials A Cassano, RL Marchese Robinson, A Palczewska, T Puzyn, A Gajewicz, ... Alternatives to Laboratory Animals 44, 2016 | 34 | 2016 |
| An ISA-TAB-Nano based data collection framework to support data-driven modelling of nanotoxicology RLM Robinson, MTD Cronin, AN Richarz, R Rallo Beilstein journal of nanotechnology 6 (1), 1978-1999, 2015 | 32 | 2015 |
| Development of computational models for the prediction of the toxicity of nanomaterials AN Richarz, JC Madden, RL Marchese Robinson, Ł Lubiński, E Mokshina, ... Perspectives in Science 3 (1-4), 27-29, 2015 | 30 | 2015 |
| Evaluation of Force-Field Calculations of Lattice Energies on a Large Public Dataset, Assessment of Pharmaceutical Relevance and Comparison to Density Functional Theory RL Marchese Robinson, D Geatches, C Morris, R Mackenzie, ... Journal of Chemical Information and Modeling, 2019 | 25 | 2019 |
| Compilation of Data and Modelling of Nanoparticle Interactions and Toxicity in the NanoPUZZLES Project AN Richarz, A Avramopoulos, E Benfenati, A Gajewicz, NG Bakhtyari, ... Modelling the Toxicity of Nanoparticles, 303-324, 2017 | 17 | 2017 |
| A cross-industry collaboration to assess if acute oral toxicity (Q) SAR models are fit-for-purpose for GHS classification and labelling J Bercu, MJ Masuda‐Herrera, A Trejo-Martin, C Hasselgren, J Lord, ... Regulatory Toxicology and Pharmacology, 104843, 2020 | 14 | 2020 |
| Machine learning predictions of concentration-specific aggregate hazard scores of inorganic nanomaterials in embryonic zebrafish C Gousiadou, RL Marchese Robinson, M Kotzabasaki, P Doganis, ... Nanotoxicology, 1-31, 2021 | 13 | 2021 |
| Off-the-shelf DFT-DISPersion methods: Are they now “on-trend” for organic molecular crystals? D Geatches, I Rosbottom, RL Marchese Robinson, P Byrne, P Hasnip, ... Journal of Chemical Physics 151, 044106, 2019 | 11 | 2019 |
Anna PalczewskaLeeds Beckett UniversityVerified email at leedsbeckett.ac.uk
