Quantitative analysis of high‐throughput biological data.
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- WIREs: Computational Molecular Science, 2023, v. 13, n. 4, p. 1, doi. 10.1002/wcms.1658
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- Article
Works matching IS 17590876 AND DT 2023 AND VI 13 AND IP 4
Results: 8
1
2
Universal QM/MM approaches for general nanoscale applications.
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- WIREs: Computational Molecular Science, 2023, v. 13, n. 4, p. 1, doi. 10.1002/wcms.1656
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- Publication type:
- Article
3
Atomistic simulations of pristine and nanoparticle reinforced hydrogels: A review.
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- WIREs: Computational Molecular Science, 2023, v. 13, n. 4, p. 1, doi. 10.1002/wcms.1655
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- Publication type:
- Article
4
Rational design of catalysts with earth‐abundant elements.
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- WIREs: Computational Molecular Science, 2023, v. 13, n. 4, p. 1, doi. 10.1002/wcms.1654
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- Publication type:
- Article
5
Combining machine‐learning and molecular‐modeling methods for drug‐target affinity predictions.
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- WIREs: Computational Molecular Science, 2023, v. 13, n. 4, p. 1, doi. 10.1002/wcms.1653
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- Article
6
Perspective: Simultaneous treatment of relativity, correlation, and QED.
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- WIREs: Computational Molecular Science, 2023, v. 13, n. 4, p. 1, doi. 10.1002/wcms.1652
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- Article
7
Graph neural networks for conditional de novo drug design.
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- WIREs: Computational Molecular Science, 2023, v. 13, n. 4, p. 1, doi. 10.1002/wcms.1651
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- Article
8
Issue Information.
- Published in:
- WIREs: Computational Molecular Science, 2023, v. 13, n. 4, p. 1, doi. 10.1002/wcms.1627
- Publication type:
- Article