The DOI matches its Crossref record; 41 of the 41 references it cites were found in a registry or an index.
The BioPlex Network: A Systematic Exploration of the Human Interactome
Open accessAbstract
Protein interactions form a network whose structure drives cellular function and whose organization informs biological inquiry. Using high-throughput affinity-purification mass spectrometry, we identify interacting partners for 2,594 human proteins in HEK293T cells. The resulting network (BioPlex) contains 23,744 interactions among 7,668 proteins with 86% previously undocumented. BioPlex accurately depicts known complexes, attaining 80%-100% coverage for most CORUM complexes. The network readily subdivides into communities that correspond to complexes or clusters of functionally related proteins. More generally, network architecture reflects cellular localization, biological process, and molecular function, enabling functional characterization of thousands of proteins. Network structure also reveals associations among thousands of protein domains, suggesting a basis for examining structurally related proteins. Finally, BioPlex, in combination with other approaches, can be used to reveal interactions of biological or clinical significance. For example, mutations in the membrane protein VAPB implicated in familial amyotrophic lateral sclerosis perturb a defined community of interactors.
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In the citing paper
“It comprises two sub-assemblies: Retriever composed of VPS35L, VPS26C, and VPS29; and the CCC complex which contains twelve subunits: COMMD1-COMMD10 and the coiled-coil domain-containing (CCDC) proteins CCDC22 and CCDC93.”
From Structure of the endosomal Commander complex linked to Ritscher-Schinzel syndrome (2023) · cites this paper as [19]
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In the citing paper
“The CCC complex comprises twelve components, the coiled coil domain-containing proteins CCDC22 and CCDC93 and ten COMMD (copper metabolism MURR1 [Mouse U2af1-rs1 region 1) domain) family members COMMD1-COMMD10.2,16,17,18,19”
From Structure of the endosomal Commander complex linked to Ritscher-Schinzel syndrome (2023) · cites this paper as [19]
Experimental — accuracy not yet measuredIn the citing paper
“The community detection approach was well illustrated in recent analyses of protein-protein interaction networks in yeast (Dutkowski et al., 2013) and human (Huttlin et al., 2015).”
From Mapping the multiscale structure of biological systems (2021) · cites this paper as Huttlin et al., 2015
In the citing paper
“In the human study, the authors first performed clique percolation to determine high-level protein communities; subsequently, they ran modularity-based clustering to further subdivide these communities into more granular subsystems, resulting in a multi-layer hierarchical structure (Figure 3A).”
From Mapping the multiscale structure of biological systems (2021) · cites this paper as Huttlin et al., 2015
In the citing paper
“several high throughput studies using robust affinity purification-mass spectrometry methodologies to elucidate protein interaction networks have revealed the interaction of ABCD1 with AT2B2 [ 167 ] and ABCD3 with AT2B2 and AT2A2 [ 168 , 169 ]”
From Peroxisomal ABC Transporters: An Update (2021) · cites this paper as [169]
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Cites
Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing
Benjamini, Y., & Hochberg, Y. (1995) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/j.2517-6161.1995.tb02031.x · Cited by 109,482 · cited 1×
“This process was repeated for all domain pairs, and p values were adjusted for multiple hypothesis testing (Benjamini and Hochberg, 1995).”
Emergence of Scaling in Random Networks
Barabási, A.-L., & Albert, R. (1999) · Science · doi:10.1126/science.286.5439.509 · Cited by 36,135 · cited 1×
“…fraction of proteins observed across the range of vertex degrees follows a linear trend for degrees above 4 that is consistent with power law behavior typical of scale-free networks (Barabasi and Albert, 1999) and has been observed in protein interaction and metabolic networks (Vidal et al., 2011).”
Eng, J. K., McCormack, A. L., & Yates, J. R. (1994) · Journal of the American Society for Mass Spectrometry · doi:10.1016/1044-0305(94)80016-2 · Cited by 6,484 · cited 1×
“Using Sequest (Eng et al., 1994), spectra were searched against human protein sequences from Uniprot (Magrane and Consortium, 2011) and common contaminants.”
Pfam: the protein families database
Finn, R. D., Bateman, A., Clements, J., Coggill, P., Eberhardt, R. Y., Eddy, S. R., Heger, A., Hetherington, K., Holm, L., Mistry, J., et al. (2014) · Nucleic Acids Research · doi:10.1093/nar/gkt1223 · Cited by 6,148
Fast algorithm for detecting community structure in networks
Newman, M. E. J. (2004) · Physical Review E · doi:10.1103/physreve.69.066133 · Cited by 5,415 · cited 1×
“We have employed a two-stage strategy to map BioPlex community structure, using clique percolation (Palla et al., 2005) to identify 256 communities that were further subdivided via modularity-based clustering (Newman, 2004) (legend continued on next page) subcommunities (Table S3).”
Uncovering the overlapping community structure of complex networks in nature and society
Palla, G., Derényi, I., Farkas, I., & Vicsek, T. (2005) · Nature · doi:10.1038/nature03607 · Cited by 5,373 · cited 2×
“We have employed a two-stage strategy to map BioPlex community structure, using clique percolation (Palla et al., 2005) to identify 256 communities that were further subdivided via modularity-based clustering (Newman, 2004) (legend continued on next page) subcommunities (Table S3).”
Warde-Farley, D., Donaldson, S. L., Comes, O., Zuberi, K., Badrawi, R., Chao, P., Franz, M., Grouios, C., Kazi, F., Lopes, C. T., et al. (2010) · Nucleic Acids Research · doi:10.1093/nar/gkq537 · Cited by 4,835 · cited 6×
“To enable more extensive comparison, we compiled all human physical interactions reported in CORUM, BioGRID (Stark et al., 2011), GeneMania, STRING, and MINT (Licata et al., 2012).”
InfluentialFunctional organization of the yeast proteome by systematic analysis of protein complexes
Gavin, A., Böesche, M., Krause, R., Grandi, P., Marzioch, M., Bauer, A., Schultz, J., Rick, J. M., Michon, A., Cruciat, C., et al. (2002) · Nature · doi:10.1038/415141a · Cited by 4,729 · cited 2×
“AP-MS has previously mapped a substantial fraction of yeast (Gavin et al., 2002; Ho et al., 2002; Krogan et al., 2006) and Drosophila (Guruharsha et al.”
STRING v9.1: protein-protein interaction networks, with increased coverage and integration
Franceschini, A., Szklarczyk, D., Frankild, S., Kuhn, M., Simonovic, M., Roth, A., Lin, J., Minguez, P., Bork, P., von Mering, C., et al. (2012) · Nucleic Acids Research · doi:10.1093/nar/gks1094 · Cited by 4,398 · cited 7×
“To enable more extensive comparison, we compiled all human physical interactions reported in CORUM, BioGRID (Stark et al., 2011), GeneMania, STRING, and MINT (Licata et al., 2012).”
InfluentialElias, J. E., & Gygi, S. P. (2007) · Nature Methods · doi:10.1038/nmeth1019 · Cited by 3,925 · cited 2×
“The target-decoy method (Elias and Gygi, 2007) was used to filter each LC-MS dataset to a preliminary 1% protein FDR.”
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CCDC32 stabilizes clathrin-coated pits and drives their invagination
Yang, Z., Yang, C., Huang, Z., Xu, P., Li, Y., Han, L., Peng, L., Wei, X., Pak, J. E., Svitkina, T., et al. (2026) · eLife · doi:10.7554/elife.107039.3 · Cited by 3
Metadata
- Authors
- Huttlin, E. L., Ting, L., Bruckner, R. J., Gebreab, F., Gygi, M. P., Szpyt, J., Tam, S., Zarraga, G., Colby, G., Baltier, K., Dong, R., Guarani, V., Vaites, L. P., Ordureau, A., Rad, R., Erickson, B. K., Wühr, M., Chick, J., Zhai, B., Kolippakkam, D., Mintseris, J., Obar, R. A., Harris, T., Artavanis-Tsakonas, S., Sowa, M. E., De Camilli, P., Paulo, J. A., Harper, J. W., & Gygi, S. P.
- Affiliations
- Harvard University (US)
- Howard Hughes Medical Institute (US)
- Biogen (United States) (US)
- Corresponding author
- Harper, J. Wade
- Gygi, Steven P.
- ORCID
- Venue
- Cell
- Publisher
- Elsevier BV
- Published
- 2015-07
- Volume
- 162
- Issue
- 2
- Pages
- 425-440
- ISSN
- 0092-8674 (ISSN-L)
- PMC
- PMC4617211
- OpenAlex
- W1611787727
- Cited by
- 1,425
- References
- 41
- Citations by year
- 2026: 46 · 2025: 82 · 2024: 116 · 2023: 105 · 2022: 98 · 2021: 162 · 2020: 159 · 2019: 197 · 2018: 171 · 2017: 147 · 2016: 122 · 2015: 18
- FWCI
- 66.47
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- Cell (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- Funders
- Howard Hughes Medical Institute
- Damon Runyon Cancer Research Foundation
- Biogen
- Charles A. King Trust
- National Institutes of Health (HG006673)
- National Human Genome Research Institute (U41HG006673)
- National Institute of Diabetes and Digestive and Kidney Diseases (K01DK098285)
- National Institute of Neurological Disorders and Stroke (R37NS036251)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bioinformatics and Genomic Networks
- Physical Sciences › Chemistry › Spectroscopy › Advanced Proteomics Techniques and Applications
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Cell Biology › Biotin and Related Studies
- Keywords
- BioPlex, human interactome, protein-protein interaction, protein complexes, protein domain interactions, community structure, HEK293T cells, VAPB, amyotrophic lateral sclerosis
- MeSH terms
- Amyotrophic Lateral Sclerosis, Humans, Proteins, Mass Spectrometry, Protein Interaction Mapping, Proteomics, Protein Interaction Maps
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