Is the reductionist paradox an Achilles Heel of drug discovery?
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- Journal of Computer-Aided Molecular Design, 2022, v. 36, n. 5, p. 329, doi. 10.1007/s10822-022-00457-2
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- Article
Works matching IS 0920654X AND DT 2022 AND VI 36 AND IP 5
Results: 8
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Evolution of Support Vector Machine and Regression Modeling in Chemoinformatics and Drug Discovery.
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- Journal of Computer-Aided Molecular Design, 2022, v. 36, n. 5, p. 355, doi. 10.1007/s10822-022-00442-9
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- Article
3
Hit diffusion: limitations to drug discovery and structure-based design.
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- Journal of Computer-Aided Molecular Design, 2022, v. 36, n. 5, p. 373, doi. 10.1007/s10822-021-00425-2
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- Article
4
Simplified, interpretable graph convolutional neural networks for small molecule activity prediction.
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- Journal of Computer-Aided Molecular Design, 2022, v. 36, n. 5, p. 391, doi. 10.1007/s10822-021-00421-6
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- Article
5
Comparing classification models—a practical tutorial.
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- Journal of Computer-Aided Molecular Design, 2022, v. 36, n. 5, p. 381, doi. 10.1007/s10822-021-00417-2
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- Article
6
Progress on open chemoinformatic tools for expanding and exploring the chemical space.
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- Journal of Computer-Aided Molecular Design, 2022, v. 36, n. 5, p. 341, doi. 10.1007/s10822-021-00399-1
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- Article
7
The power of a mentor.
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- Journal of Computer-Aided Molecular Design, 2022, v. 36, n. 5, p. 339, doi. 10.1007/s10822-021-00398-2
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- Article
8
Fine-tuning of a generative neural network for designing multi-target compounds.
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- Journal of Computer-Aided Molecular Design, 2022, v. 36, n. 5, p. 363, doi. 10.1007/s10822-021-00392-8
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- Article