The DOI matches its Crossref record; 112 of the 112 references it cites were found in a registry or an index.
Network pharmacology applications to map the unexplored target space and therapeutic potential of natural products
Abstract
This article reviews key network pharmacology concepts and recent experimental–computational approaches that have been successfully applied to natural product research, including unbiased elucidation of mechanisms of action and systematic prediction of effective therapeutic combinations.
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Cites
1 retracted
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ChEMBL: a large-scale bioactivity database for drug discovery
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Can the pharmaceutical industry reduce attrition rates?
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How many drug targets are there?
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Natural products in drug discovery
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Cited by
Wu, P., Chang, C., Zhu, G., Zhai, L., Zhang, X., Huan, Q., Gao, Z., Deng, H., Liang, Y., & Xiao, H. (2023) · Drug Design, Development and Therapy · doi:10.2147/dddt.s407339 · Cited by 7
Metadata
- Authors
- Kibble, M., Saarinen, N., Tang, J., Wennerberg, K., Mäkelä, S., & Aittokallio, T.
- Venue
- Natural Product Reports
- Publisher
- Royal Society of Chemistry (RSC)
- Published
- 2015
- Volume
- 32
- Issue
- 8
- Pages
- 1249-1266
- ISSN
- 0265-0568 (ISSN-L)
- 1460-4752
- OpenAlex
- W1906327883
- Cited by
- 489
- References
- 112
- FWCI
- 16.97
- Type
- journal article
- Language
- en
- Open access
- closed
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- CoChat. (2026). Citation check: Network pharmacology applications to map the unexplored target space and therapeutic potential of natural products. https://app.cochat.ai/papers/10.1039/c5np00005j
- The paper
- Kibble, M., Saarinen, N., Tang, J., Wennerberg, K., Mäkelä, S., & Aittokallio, T. (2015). Network pharmacology applications to map the unexplored target space and therapeutic potential of natural products. Natural Product Reports. https://doi.org/10.1039/c5np00005j
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.
