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Filip Miljkovic
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2020 – today
- 2024
- [j6]Ya Chen
, Thomas Seidel
Active Learning Approach for Guiding Site-of-Metabolism Measurement and Annotation. J. Chem. Inf. Model. 64(2): 348-358 (2024) - 2023
- [j5]Peizhen Bai
Interpretable bilinear attention network with domain adaptation improves drug-target prediction. Nat. Mac. Intell. 5(2): 126-136 (2023) - [d6]Elena Xerxa, Filip Miljkovic
Protein kinase inhibitors. Zenodo, 2023 - 2022
- [j4]Andrés Martínez Mora, Vigneshwari Subramanian
Multi-task convolutional neural networks for predicting in vitro clearance endpoints from molecular images. J. Comput. Aided Mol. Des. 36(6): 443-457 (2022) - [d5]Atsushi Yoshimori
Candidate compounds from the design of covalent Bruton's tyrosine kinase (BTK) inhibitors via focused deep generative modeling. Zenodo, 2022 - [i1]Peizhen Bai, Filip Miljkovic, Bino John, Haiping Lu:
Interpretable bilinear attention network with domain adaptation improves drug-target prediction. CoRR abs/2208.02194 (2022) - 2021
- [c1]Peizhen Bai
Hierarchical Clustering Split for Low-Bias Evaluation of Drug-Target Interaction Prediction. BIBM 2021: 641-644 - 2020
- [j3]Filip Miljkovic
Data structures for computational compound promiscuity analysis and exemplary applications to inhibitors of the human kinome. J. Comput. Aided Mol. Des. 34(1): 1-10 (2020) - [j2]Raquel Rodríguez-Pérez
Assessing the information content of structural and protein-ligand interaction representations for the classification of kinase inhibitor binding modes via machine learning and active learning. J. Cheminformatics 12(1): 36 (2020)
2010 – 2019
- 2019
- [j1]Filip Miljkovic
Systematic computational identification of promiscuity cliff pathways formed by inhibitors of the human kinome. J. Comput. Aided Mol. Des. 33(6): 559-572 (2019) - [d4]Christian Feldmann, Filip Miljkovic, Dimitar G. Yonchev, Jürgen Bajorath
Promiscuous compounds with activity against different target classes. Zenodo, 2019 - [d3]Filip Miljkovic, Jürgen Bajorath
Promiscuity cliffs (PCs), promiscuity cliff pathways (PCPs), and promiscuity hubs (PHs) formed by inhibitors of human kinases. Zenodo, 2019 - [d2]Filip Miljkovic, Raquel Rodríguez-Pérez, Jürgen Bajorath
Machine Learning Models for Predicting Kinase Inhibitors with Different Binding Modes. Zenodo, 2019 - [d1]Filip Miljkovic, Raquel Rodríguez-Pérez, Jürgen Bajorath
Machine Learning Models for Predicting Kinase Inhibitors with Different Binding Modes. Zenodo, 2019
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last updated on 2024-11-15 20:40 CET by the dblp team
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