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ORCIDSabina Podlewska
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2020 – today
- 2024
[j17]Ewelina Jamrozik, Marek Smieja, Sabina Podlewska
:
ADMET-PrInt: Evaluation of ADMET Properties: Prediction and Interpretation. J. Chem. Inf. Model. 64(5): 1425-1432 (2024)- 2023
- [j16]Agnieszka Wojtuch, Tomasz Danel, Sabina Podlewska, Lukasz Maziarka:
Extended study on atomic featurization in graph neural networks for molecular property prediction. J. Cheminformatics 15(1): 81 (2023) - [j15]Tobiasz Cieplinski, Tomasz Danel, Sabina Podlewska, Stanislaw Jastrzebski:
Generative Models Should at Least Be Able to Design Molecules That Dock Well: A New Benchmark. J. Chem. Inf. Model. 63(11): 3238-3247 (2023) - [i3]Tomasz Danel, Jan Leski, Sabina Podlewska, Igor T. Podolak:
Docking-based generative approaches in the search for new drug candidates. CoRR abs/2312.13944 (2023) - 2022
- [i2]Jarek Duda, Sabina Podlewska:
Low cost prediction of probability distributions of molecular properties for early virtual screening. CoRR abs/2207.11174 (2022) - 2021
- [j14]Agnieszka Wojtuch, Rafal Jankowski, Sabina Podlewska:
How can SHAP values help to shape metabolic stability of chemical compounds? J. Cheminformatics 13(1): 74 (2021) - [c1]Agnieszka Pocha, Tomasz Danel, Sabina Podlewska, Jacek Tabor, Lukasz Maziarka:
Comparison of Atom Representations in Graph Neural Networks for Molecular Property Prediction. IJCNN 2021: 1-8 - 2020
- [j13]Krzysztof Rajda, Sabina Podlewska:
Similar, or dissimilar, that is the question. How different are methods for comparison of compounds similarity? Comput. Biol. Chem. 88: 107367 (2020) - [j12]Stanislaw Jastrzebski, Maciej Szymczak, Agnieszka Pocha, Stefan Mordalski, Jacek Tabor, Andrzej J. Bojarski, Sabina Podlewska:
Emulating Docking Results Using a Deep Neural Network: A New Perspective for Virtual Screening. J. Chem. Inf. Model. 60(9): 4246-4262 (2020) - [i1]Tobiasz Cieplinski, Tomasz Danel, Sabina Podlewska, Stanislaw Jastrzebski:
We should at least be able to Design Molecules that Dock Well. CoRR abs/2006.16955 (2020)
2010 – 2019
- 2019
- [j11]Damian Lesniak, Sabina Podlewska, Stanislaw Jastrzebski, Igor Sieradzki, Andrzej J. Bojarski, Jacek Tabor:
Development of New Methods Needs Proper Evaluation - Benchmarking Sets for Machine Learning Experiments for Class A GPCRs. J. Chem. Inf. Model. 59(12): 4974-4992 (2019) - 2017
- [j10]Sabina Podlewska, Wojciech M. Czarnecki, Rafal Kafel, Andrzej J. Bojarski:
Creating the New from the Old: Combinatorial Libraries Generation with Machine-Learning-Based Compound Structure Optimization. J. Chem. Inf. Model. 57(2): 133-147 (2017) - 2015
- [j9]Stefan Mordalski, Jagna Witek, Sabina Smusz, Krzysztof Rataj, Andrzej J. Bojarski:
Multiple conformational states in retrospective virtual screening - homology models vs. crystal structures: beta-2 adrenergic receptor case study. J. Cheminformatics 7: 13 (2015) - [j8]Wojciech M. Czarnecki, Sabina Podlewska, Andrzej J. Bojarski:
Robust optimization of SVM hyperparameters in the classification of bioactive compounds. J. Cheminformatics 7: 38:1-38:15 (2015) - [j7]Sabina Smusz, Stefan Mordalski, Jagna Witek, Krzysztof Rataj, Rafal Kafel, Andrzej J. Bojarski:
Multi-Step Protocol for Automatic Evaluation of Docking Results Based on Machine Learning Methods - A Case Study of Serotonin Receptors 5-HT6 and 5-HT7. J. Chem. Inf. Model. 55(4): 823-832 (2015) - 2014
- [j6]Rafal Kurczab, Sabina Smusz, Andrzej J. Bojarski:
The influence of negative training set size on machine learning-based virtual screening. J. Cheminformatics 6(1): 32 (2014) - 2013
- [j5]Sabina Smusz, Rafal Kurczab, Andrzej J. Bojarski:
The influence of the inactives subset generation on the performance of machine learning methods. J. Cheminformatics 5: 17 (2013) - [j4]Sabina Smusz, Rafal Kurczab, Andrzej J. Bojarski:
The influence of hashed fingerprints density on the machine learning methods performance. J. Cheminformatics 5(S-1): 25 (2013) - [j3]Jagna Witek, Krzysztof Rataj, Stefan Mordalski, Sabina Smusz, Tomasz Kosciólek, Andrzej J. Bojarski:
Application of Structural Interaction Fingerpints (SIFts) into post-docking analysis - insight into activity and selectivity. J. Cheminformatics 5(S-1): 28 (2013) - [j2]Rafal Kurczab, Sabina Smusz, Andrzej J. Bojarski:
The influence of training actives/inactives ratio on machine learning performance. J. Cheminformatics 5(S-1): 30 (2013) - 2011
- [j1]Rafal Kurczab, Sabina Smusz, Andrzej J. Bojarski:
Evaluation of different machine learning methods for ligand-based virtual screening. J. Cheminformatics 3(S-1): 41 (2011)
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