The DOI matches its Crossref record; 126 of the 126 references it cites were found in a registry or an index.
Deciphering Protein–Protein Interactions. Part I. Experimental Techniques and Databases
Open accessAbstract
roteins interact with each other in a highly specific manner, and protein interactions play a key role in many cellular processes; in particular, the distortion of protein interfaces may lead to the development of many diseases.To understand the mechanisms of protein recognition at the molecular level and to unravel the global picture of protein interactions in the cell, different experimental techniques have been developed.Some methods characterize individual protein interactions while others are advanced for screening interactions on a genomewide scale.In this review we describe different experimental techniques of protein interaction identification together with various databases which attempt to classify the large array of experimental data.We discuss the main promises and pitfalls of different methods and present several approaches to verify and validate the diverse experimental data produced by highthroughput techniques.
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
Cluster analysis and display of genome-wide expression patterns
Eisen, M. B., Spellman, P. T., Brown, P. O., & Botstein, D. (1998) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.95.25.14863 · Cited by 16,184
Mass spectrometry-based proteomics
Aebersold, R., & Mann, M. (2003) · Nature · doi:10.1038/nature01511 · Cited by 6,955
A novel genetic system to detect protein–protein interactions
Fields, S., & Song, O.-K. (1989) · Nature · doi:10.1038/340245a0 · Cited by 6,114
Laser desorption ionization of proteins with molecular masses exceeding 10,000 daltons
Karas, M., & Hillenkamp, F. (1988) · Analytical Chemistry · doi:10.1021/ac00171a028 · Cited by 5,637
Functional organization of the yeast proteome by systematic analysis of protein complexes
Gavin, A.-C., Bösche, M., Krause, R., Grandi, P., Marzioch, M., Bauer, A., Schultz, J., Rick, J. M., Michon, A.-M., Cruciat, C.-M., et al. (2002) · Nature · doi:10.1038/415141a · Cited by 4,759
A comprehensive analysis of protein–protein interactions in Saccharomyces cerevisiae
Uetz, P., Giot, L., Cagney, G., Mansfield, T. A., Judson, R. S., Knight, J. R., Lockshon, D., Narayan, V., Srinivasan, M., Pochart, P., et al. (2000) · Nature · doi:10.1038/35001009 · Cited by 4,706
Smith, G. P. (1985) · Science · doi:10.1126/science.4001944 · Cited by 4,143
BioGRID: a general repository for interaction datasets
Stark, C. (2006) · Nucleic Acids Research · doi:10.1093/nar/gkj109 · Cited by 3,960
Systematic identification of protein complexes in Saccharomyces cerevisiae by mass spectrometry
Ho, Y., Gruhler, A., Heilbut, A., Bader, G. D., Moore, L., Adams, S.-L., Millar, A., Taylor, P., Bennett, K., Boutilier, K., et al. (2002) · Nature · doi:10.1038/415180a · Cited by 3,601
A comprehensive two-hybrid analysis to explore the yeast protein interactome
Ito, T., Chiba, T., Ozawa, R., Yoshida, M., Hattori, M., & Sakaki, Y. (2001) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.061034498 · Cited by 3,566
Cited by
Structure-based prediction of protein–protein interactions on a genome-wide scale
Zhang, Q. C., Petrey, D., Deng, L., Qiang, L., Shi, Y., Thu, C. A., Bisikirska, B., Lefebvre, C., Accili, D., Hunter, T., et al. (2012) · Nature · doi:10.1038/nature11503 · Cited by 723
ATTED-II provides coexpressed gene networks for Arabidopsis
Obayashi, T., Hayashi, S., Saeki, M., Ohta, H., & Kinoshita, K. (2009) · Nucleic Acids Research · doi:10.1093/nar/gkn807 · Cited by 366
Shoemaker, B. A., & Panchenko, A. R. (2007) · PLoS Computational Biology · doi:10.1371/journal.pcbi.0030043 · Cited by 332
Self-citationProtein interface conservation across structure space
Zhang, Q. C., Petrey, D., Norel, R., & Honig, B. H. (2010) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1005894107 · Cited by 156
Targeting Protein–Protein Interactions and Fragment-Based Drug Discovery
Valkov, E., Sharpe, T., Marsh, M., Greive, S., & Hyvönen, M. (2011) · Topics in Current Chemistry · doi:10.1007/128_2011_265 · Cited by 107
Metadata
- Authors
- Shoemaker, B. A., & Panchenko, A. R.
- Venue
- PLoS Computational Biology
- Publisher
- Public Library of Science (PLoS)
- Published
- 2007-03-30
- Volume
- 3
- Issue
- 3
- Pages
- e42
- ISSN
- 1553-734X (ISSN-L)
- 1553-7358
- OpenAlex
- W2001457899
- Cited by
- 398
- References
- 126
- FWCI
- 13.29
- Type
- journal article
- Language
- en
- Open access
- gold
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: Deciphering Protein–Protein Interactions. Part I. Experimental Techniques and Databases. https://app.cochat.ai/papers/10.1371/journal.pcbi.0030042
- The paper
- Shoemaker, B. A., & Panchenko, A. R. (2007). Deciphering Protein–Protein Interactions. Part I. Experimental Techniques and Databases. PLoS Computational Biology. https://doi.org/10.1371/journal.pcbi.0030042
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.
