The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.
Novel trends in high-throughput screening
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Citations
Cites
Zhang, J.-H., Chung, T. D. Y., & Oldenburg, K. R. (1999) · SLAS Discovery · doi:10.1177/108705719900400206 · Cited by 6,847
In Vivo Activation of the p53 Pathway by Small-Molecule Antagonists of MDM2
Vassilev, L. T., Vu, B. T., Graves, B., Carvajal, D., Podlaski, F., Filipovic, Z., Kong, N., Kammlott, U., Lukacs, C., Klein, C., et al. (2004) · Science · doi:10.1126/science.1092472 · Cited by 4,661
How many drug targets are there?
Overington, J. P., Al-Lazikani, B., & Hopkins, A. L. (2006) · Nature Reviews Drug Discovery · doi:10.1038/nrd2199 · Cited by 3,505
Structural basis for high-affinity peptide inhibition of p53 interactions with MDM2 and MDMX
Pazgier, M., Liu, M., Zou, G., Yuan, W., Li, C., Li, C., Li, J., Monbo, J., Zella, D., Tarasov, S. G., et al. (2009) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0900947106 · Cited by 391
Cited by
Enumeration of 166 Billion Organic Small Molecules in the Chemical Universe Database GDB-17
Ruddigkeit, L., van Deursen, R., Blum, L. C., & Reymond, J.-L. (2012) · Journal of Chemical Information and Modeling · doi:10.1021/ci300415d · Cited by 1,505
Rethinking drug design in the artificial intelligence era
Schneider, P., Walters, W. P., Plowright, A. T., Sieroka, N., Listgarten, J., Goodnow, R. A., Fisher, J., Jansen, J. M., Duca, J. S., Rush, T. S., et al. (2020) · Nature Reviews Drug Discovery · doi:10.1038/s41573-019-0050-3 · Cited by 894
Reymond, J.-L. (2015) · Accounts of Chemical Research · doi:10.1021/ar500432k · Cited by 720
A practical guide to large-scale docking
Bender, B. J., Gahbauer, S., Luttens, A., Lyu, J., Webb, C. M., Stein, R. M., Fink, E. A., Balius, T. E., Carlsson, J., Irwin, J. J., et al. (2021) · Nature Protocols · doi:10.1038/s41596-021-00597-z · Cited by 546
Could 3D models of cancer enhance drug screening?
Brancato, V., Oliveira, J. M., Correlo, V. M., Reis, R. L., & Kundu, S. C. (2020) · Biomaterials · doi:10.1016/j.biomaterials.2019.119744 · Cited by 281
Metadata
- Authors
- Mayr, L. M., & Bojanic, D.
- Venue
- Current Opinion in Pharmacology
- Publisher
- Elsevier BV
- Published
- 2009-10
- Volume
- 9
- Issue
- 5
- Pages
- 580-588
- ISSN
- 1471-4892 (ISSN-L)
- OpenAlex
- W2046588282
- Cited by
- 694
- References
- 4
- FWCI
- 38.31
- Type
- journal article
- Language
- en
- Open access
- closed
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
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- CoChat. (2026). Citation check: Novel trends in high-throughput screening. https://app.cochat.ai/papers/10.1016/j.coph.2009.08.004
- The paper
- Mayr, L. M., & Bojanic, D. (2009). Novel trends in high-throughput screening. Current Opinion in Pharmacology. https://doi.org/10.1016/j.coph.2009.08.004
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
