The DOI matches its Crossref record.
Reverse-phase protein lysate microarrays for cell signaling analysis
Abstract
'Reverse-phase' protein lysate microarray (RPA) assays use micro-scale, cell lysate dot blots that are printed to a substrate, followed by quantitative immunochemical protein detection, known to be particularly effective across many samples. Large-scale sample collection is a labor-intensive and time-consuming process; the information yielded from RPA assays, however, provides unique opportunities to experimentally interpret theoretical protein networks quantitatively. When specific antibodies are used, RPA can generate 1,000 times more data points using 10,000 times less sample volume than an ordinary western blot, enabling researchers to monitor quantitative proteomic responses for various time-scale and input-dose gradients simultaneously. Hence, the RPA system can be an excellent method for experimental validation of theoretical protein network models. Besides the initial screening of primary antibodies, collection of several hundreds of sample lysates from 1- to 8-h periods can be completed in ∼10 d; subsequent RPA printing and signal detection steps require an additional 2–3 d.
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
Cited by
The Molecular Signatures Database Hallmark Gene Set Collection
Liberzon, A., Birger, C., Thorvaldsdóttir, H., Ghandi, M., Mesirov, J. P., & Tamayo, P. (2015) · Cell Systems · doi:10.1016/j.cels.2015.12.004 · Cited by 13,807
TCPA: a resource for cancer functional proteomics data
Li, J., Lu, Y., Akbani, R., Ju, Z., Roebuck, P. L., Liu, W., Yang, J.-Y., Broom, B. M., Verhaak, R. G. W., Kane, D. W., et al. (2013) · Nature Methods · doi:10.1038/nmeth.2650 · Cited by 512
Integrated Analysis of Transcriptomic and Proteomic Data
Haider, S., & Pal, R. (2013) · Current Genomics · doi:10.2174/1389202911314020003 · Cited by 431
Metadata
- Authors
- Spurrier, B., Ramalingam, S., & Nishizuka, S.
- Venue
- Nature Protocols
- Published
- 2008-10-30
- Volume
- 3
- Issue
- 11
- Pages
- 1796-1808
- ISSN
- 1750-2799 (ISSN-L)
- 1754-2189
- OpenAlex
- W2068123273
- Cited by
- 181
- References
- 0
- FWCI
- 4.59
- 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.
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: Reverse-phase protein lysate microarrays for cell signaling analysis. https://app.cochat.ai/papers/10.1038/nprot.2008.179
- The paper
- Spurrier, B., Ramalingam, S., & Nishizuka, S. (2008). Reverse-phase protein lysate microarrays for cell signaling analysis. Nature Protocols. https://doi.org/10.1038/nprot.2008.179
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.