The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
Localization of Organelle Proteins by Isotope Tagging (LOPIT)
Open accessAbstract
We describe a proteomics method for determining the subcellular localization of membrane proteins. Organelles are partially separated using centrifugation through self-generating density gradients. Proteins from each organelle co-fractionate and therefore exhibit similar distributions in the gradient. Protein distributions can be determined through a series of pair-wise comparisons of gradient fractions, using cleavable ICAT to enable relative quantitation of protein levels by MS. The localization of novel proteins is determined using multivariate data analysis techniques to match their distributions to those of proteins that are known to reside in specific organelles. Using this approach, we have simultaneously demonstrated the localization of membrane proteins in both the endoplasmic reticulum and the Golgi apparatus in Arabidopsis. Localization of organelle proteins by isotope tagging is a new tool for high-throughput protein localization, which is applicable to a wide range of research areas such as the study of organelle function and protein trafficking.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
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 · cited 1×
“ICAT enables the relative quantitation of protein levels in two samples by MS ( 12 ).”
Proteomic characterization of the human centrosome by protein correlation profiling
Andersen, J. S., Wilkinson, C. J., Mayor, T., Mortensen, P., Nigg, E. A., & Mann, M. (2003) · Nature · doi:10.1038/nature02166 · Cited by 1,319
Cited by
A subcellular map of the human proteome
Thul, P. J., Åkesson, L., Wiking, M., Mahdessian, D., Geladaki, A., Ait Blal, H., Alm, T., Asplund, A., Björk, L., Breckels, L. M., et al. (2017) · Science · doi:10.1126/science.aal3321 · Cited by 2,813
Self-citationPectin structure and biosynthesis
MOHNEN, D. (2008) · Current Opinion in Plant Biology · doi:10.1016/j.pbi.2008.03.006 · Cited by 2,447
Quantitative, High-Resolution Proteomics for Data-Driven Systems Biology
Cox, J., & Mann, M. (2011) · Annual Review of Biochemistry · doi:10.1146/annurev-biochem-061308-093216 · Cited by 685
Global, quantitative and dynamic mapping of protein subcellular localization
Itzhak, D. N., Tyanova, S., Cox, J., & Borner, G. H. (2016) · eLife · doi:10.7554/elife.16950 · Cited by 649
Spatial proteomics: a powerful discovery tool for cell biology
Lundberg, E., & Borner, G. H. H. (2019) · Nature Reviews Molecular Cell Biology · doi:10.1038/s41580-018-0094-y · Cited by 591
Metadata
- Authors
- Dunkley, T. P. J., Watson, R., Griffin, J. L., Dupree, P., & Lilley, K. S.
- Venue
- Molecular & Cellular Proteomics
- Publisher
- Elsevier BV
- Published
- 2004-11
- Volume
- 3
- Issue
- 11
- Pages
- 1128-1134
- ISSN
- 1535-9476 (ISSN-L)
- OpenAlex
- W2129716198
- Cited by
- 352
- References
- 2
- FWCI
- 6.38
- Type
- journal article
- Language
- en
- Open access
- hybrid
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.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Localization of Organelle Proteins by Isotope Tagging (LOPIT). https://app.cochat.ai/papers/10.1074/mcp.t400009-mcp200
- The paper
- Dunkley, T. P. J., Watson, R., Griffin, J. L., Dupree, P., & Lilley, K. S. (2004). Localization of Organelle Proteins by Isotope Tagging (LOPIT). Molecular & Cellular Proteomics. https://doi.org/10.1074/mcp.t400009-mcp200
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.
