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Cited by 341

The DOI matches its Crossref record; 10 of the 10 references it cites were found in a registry or an index.

Activity-based protein profiling for biochemical pathway discovery in cancer

Open access
Nomura, Daniel K., Dix, Melissa M., Cravatt, Benjamin F.·2010·Nature Reviews Cancer

Abstract

Large-scale profiling methods have uncovered numerous gene and protein expression changes that correlate with tumorigenesis. However, determining the relevance of these expression changes and which biochemical pathways they affect has been hindered by our incomplete understanding of the proteome and its myriad functions and modes of regulation. Activity-based profiling platforms enable both the discovery of cancer-relevant enzymes and selective pharmacological probes to perturb and characterize these proteins in tumour cells. When integrated with other large-scale profiling methods, activity-based proteomics can provide insight into the metabolic and signalling pathways that support cancer pathogenesis and illuminate new strategies for disease diagnosis and treatment.

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Metadata

Authors
Nomura, D. K., Dix, M. M., & Cravatt, B. F.
Venue
Nature Reviews Cancer
Published
2010-08-12
Volume
10
Issue
9
Pages
630-638
ISSN
  • 1474-175X (ISSN-L)
  • 1474-1768
OpenAlex
W2021790986
Cited by
341
References
10
FWCI
1.24
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: Activity-based protein profiling for biochemical pathway discovery in cancer. https://app.cochat.ai/papers/10.1038/nrc2901
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Nomura, D. K., Dix, M. M., & Cravatt, B. F. (2010). Activity-based protein profiling for biochemical pathway discovery in cancer. Nature Reviews Cancer. https://doi.org/10.1038/nrc2901

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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.