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Interpretable Machine Learning Models for Molecular Design of Tyrosine Kinase Inhibitors Using Variational Autoencoders and Perturbation-Based Approach of Chemical Space Exploration
Research article (International Journal of Molecular Sciences, 2022) · cited 14× · AI/ML
Interpretable Machine Learning Models for Molecular Design of Tyrosine Kinase Inhibitors Using Variational Autoencoders and Perturbation-Based Approach of Chemical Space Exploration
Summary
Interpretable Machine Learning Models for Molecular Design of Tyrosine Kinase Inhibitors Using Variational Autoencoders and Perturbation-Based Approach of Chemical Space Exploration is a scholarly article[1].
Key Facts
Interpretable Machine Learning Models for Molecular Design of Tyrosine Kinase Inhibitors Using Variational Autoencoders and Perturbation-Based Approach of Chemical Space Exploration's instance of is recorded as scholarly article[2].
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APA4ort.xyz Knowledge Graph. (2026). Interpretable Machine Learning Models for Molecular Design of Tyrosine Kinase Inhibitors Using Variational Autoencoders and Perturbation-Based Approach of Chemical Space Exploration. Retrieved May 24, 2026, from https://4ort.xyz/entity/interpretable-machine-learning-models-for-molecular-design-of-tyrosine-kinase-inhibitors-using-variational-autoencoders-
MLA“Interpretable Machine Learning Models for Molecular Design of Tyrosine Kinase Inhibitors Using Variational Autoencoders and Perturbation-Based Approach of Chemical Space Exploration.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/interpretable-machine-learning-models-for-molecular-design-of-tyrosine-kinase-inhibitors-using-variational-autoencoders-.
BibTeX@misc{4ortxyz_interpretable-machine-learning-models-for-molecular-design-of-tyrosine-kinase-inhibitors-using-variational-autoencoders-_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Interpretable Machine Learning Models for Molecular Design of Tyrosine Kinase Inhibitors Using Variational Autoencoders and Perturbation-Based Approach of Chemical Space Exploration}}, year = {2026}, url = {https://4ort.xyz/entity/interpretable-machine-learning-models-for-molecular-design-of-tyrosine-kinase-inhibitors-using-variational-autoencoders-}, note = {Accessed: 2026-05-24}}
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