The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
A streamlined platform for high-content functional proteomics of primary human specimens
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Citations
Cites
Quantitative analysis of complex protein mixtures using isotope-coded affinity tags
Gygi, S. P., Rist, B., Gerber, S. A., Turecek, F., Gelb, M. H., & Aebersold, R. (1999) · Nature Biotechnology · doi:10.1038/13690 · Cited by 4,683
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Activity-Based Protein Profiling: From Enzyme Chemistry to Proteomic Chemistry
Cravatt, B. F., Wright, A. T., & Kozarich, J. W. (2008) · Annual Review of Biochemistry · doi:10.1146/annurev.biochem.75.101304.124125 · Cited by 1,270
Self-citationA Comprehensive Profile of Brain Enzymes that Hydrolyze the Endocannabinoid 2-Arachidonoylglycerol
Blankman, J. L., Simon, G. M., & Cravatt, B. F. (2007) · Chemistry & Biology · doi:10.1016/j.chembiol.2007.11.006 · Cited by 1,177
Self-citationMonoacylglycerol lipase regulates a fatty acid network that promotes cancer pathogenesis
Nomura, D. K., Long, J. Z., Niessen, S., Hoover, H. S., Ng, S.-W., & Cravatt, B. F. (2010) · Cell · doi:10.1016/j.cell.2009.11.027 · Cited by 1,002
Self-citationSelective blockade of 2-arachidonoylglycerol hydrolysis produces cannabinoid behavioral effects
Long, J. Z., Li, W., Booker, L., Burston, J. J., Kinsey, S. G., Schlosburg, J. E., Pavón, F. J., Serrano, A. M., Selley, D. E., Parsons, L. H., et al. (2009) · Nature Chemical Biology · doi:10.1038/nchembio.129 · Cited by 934
Self-citationEnzymatic pathways that regulate endocannabinoid signaling in the nervous system
Ahn, K., McKinney, M. K., & Cravatt, B. F. (2008) · Chemical Reviews · doi:10.1021/cr0782067 · Cited by 529
Self-citationThe serine hydrolase ABHD6 controls the accumulation and efficacy of 2-AG at cannabinoid receptors
Marrs, W. R., Blankman, J. L., Horne, E. A., Thomazeau, A., Lin, Y. H., Coy, J., Bodor, A. L., Muccioli, G. G., Hu, S. S.-J., Woodruff, G., et al. (2010) · Nature Neuroscience · doi:10.1038/nn.2601 · Cited by 441
Self-citationStrategies for Discovering and Derisking Covalent, Irreversible Enzyme Inhibitors
Johnson, D. S., Weerapana, E., & Cravatt, B. F. (2010) · Future Medicinal Chemistry · doi:10.4155/fmc.10.21 · Cited by 387
Self-citationClick Chemistry in Proteomic Investigations
Parker, C. G., & Pratt, M. R. (2020) · Cell · doi:10.1016/j.cell.2020.01.025 · Cited by 380
Weerapana, E., Speers, A. E., & Cravatt, B. F. (2007) · Nature Protocols · doi:10.1038/nprot.2007.194 · Cited by 276
Self-citationBachovchin, D. A., Ji, T., Li, W., Simon, G. M., Blankman, J. L., Adibekian, A., Hoover, H., Niessen, S., & Cravatt, B. F. (2010) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1011663107 · Cited by 274
Self-citationDAGLβ inhibition perturbs a lipid network involved in macrophage inflammatory responses
Hsu, K.-L., Tsuboi, K., Adibekian, A., Pugh, H., Masuda, K., & Cravatt, B. F. (2012) · Nature Chemical Biology · doi:10.1038/nchembio.1105 · Cited by 222
“To more comprehensively profile inhibitor selectivity in vivo , we used the LC/MS method ABPP-MudPIT 29 to measure serine hydrolase activities in macrophages from mice treated with KT109, KT172, or KT195 (2 or 5 mg per kg body weight, i.p., 4 h).”
Self-citationRudnick, P. A., Clauser, K. R., Kilpatrick, L. E., Tchekhovskoi, D. V., Neta, P., Blonder, N., Billheimer, D. D., Blackman, R. K., Bunk, D. M., Cardasis, H. L., et al. (2010) · Molecular & Cellular Proteomics · doi:10.1074/mcp.m900223-mcp200 · Cited by 183
Zhang, D., Saraf, A., Kolasa, T., Bhatia, P., Zheng, G. Z., Patel, M., Lannoye, G. S., Richardson, P., Stewart, A., Rogers, J. C., et al. (2007) · Neuropharmacology · doi:10.1016/j.neuropharm.2006.11.009 · Cited by 99
An in vivo multiplexed small-molecule screening platform
Grüner, B. M., Schulze, C. J., Yang, D., Ogasawara, D., Dix, M. M., Rogers, Z. N., Chuang, C.-H., McFarland, C. D., Chiou, S.-H., Brown, J. M., et al. (2016) · Nature Methods · doi:10.1038/nmeth.3992 · Cited by 62
Self-citationPhospholipase Cγ2 regulates endocannabinoid and eicosanoid networks in innate immune cells
Jing, H., Reed, A., Ulanovskaya, O. A., Grigoleit, J.-S., Herbst, D. M., Henry, C. L., Li, H., Barbas, S., Germain, J., Masuda, K., et al. (2021) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2112971118 · Cited by 24
Self-citation
Metadata
- Authors
- Jessani, N., Niessen, S., Wei, B. Q., Nicolau, M., Humphrey, M., Ji, Y., Han, W., Noh, D.-Y., Yates, J. R., Jeffrey, S. S., & Cravatt, B. F.
- Venue
- Nature Methods
- Published
- 2005-08-23
- Volume
- 2
- Issue
- 9
- Pages
- 691-697
- ISSN
- 1548-7091 (ISSN-L)
- 1548-7105
- OpenAlex
- W2142968843
- Cited by
- 240
- References
- 1
- FWCI
- 9.83
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
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.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
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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.
