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.
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.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The check wasn’t confident either way, so it gives no verdict — never disputed.
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]
Experimental — accuracy not yet measuredThe check wasn’t confident either way, so it gives no verdict — never disputed.
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]
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
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.”
Self-citation
Flagged first, then by citations
Cited by
Sorted by citations
Items 701–800 of 1,001
Loss-of-function variants in C3ORF52 result in localized autosomal recessive hypotrichosis
Malki, L., Sarig, O., Cesarato, N., Mohamad, J., Canter, T., Assaf, S., Pavlovsky, M., Vodo, D., Anis, Y., Bihari, O., et al. (2020) · Genetics in Medicine · doi:10.1038/s41436-020-0794-5 · Cited by 19
Huang, P., Liu, C., Gao, W., Chu, B., Cai, Z., & Tian, R. (2020) · Journal of Mass Spectrometry · doi:10.1002/jms.4653 · Cited by 17
Jiang, L., & Hu, L. G. (2020) · Oncology Letters · doi:10.3892/ol.2020.12141 · Cited by 18
RNA Pol II inhibition activates cell death independently from the loss of transcription
Harper, N. W., Birdsall, G. A., Honeywell, M. E., Ward, K. M., Pai, A. A., & Lee, M. J. (2025) · Cell · doi:10.1016/j.cell.2025.07.034 · Cited by 18
Washburn, M. P. (2016) · Genome biology · doi:10.1186/s13059-016-0913-4 · Cited by 17
“, have reported human interactomes constructed using data from HEK293T cells [1], and HeLa cells [2], respectively.”
BackgroundJiang, Y., DeBord, D., Vitrac, H., Stewart, J., Haghani, A., Eyk, J. E. V., Fert‐Bober, J., & Meyer, J. G. (2024) · Journal of Proteome Research · doi:10.1021/acs.jproteome.4c00248 · Cited by 17
TPepPro: a deep learning model for predicting peptide–protein interactions
Xiao-hong, J., Chen, Z., Yu, D., Jiang, Q., Chen, Z., Yan, B., Qin, J., Liu, Y., & Wang, J. (2024) · Bioinformatics · doi:10.1093/bioinformatics/btae708 · Cited by 18
Computational Prediction of Protein Complexes from Protein Interaction Networks
Srihari, S., Yong, C. H., & Wong, L. (2017) · doi:10.1145/3064650 · Cited by 17
Rivas, J. D. L., Alonso‐López, D., & Arroyo, M. (2017) · Advances in protein chemistry and structural biology · doi:10.1016/bs.apcsb.2017.09.002 · Cited by 17
Surles-Zeigler, M. C., Li, Y., Distel, T. J., Omotayo, H., Ge, S., & Ford, B. D. (2018) · PLoS ONE · doi:10.1371/journal.pone.0197092 · Cited by 18
Precision global health and comorbidity: a population-based study of 16 357 people in rural Uganda
Chami, G. F., Kabatereine, N. B., Tukahebwa, E. M., & Dunne, D. W. (2018) · Journal of The Royal Society Interface · doi:10.1098/rsif.2018.0248 · Cited by 17
“Pairwise relationships between a type of molecular marker or phenotype, such as genes [11], proteins [12], metabolites [13], symptoms [14] and clinical diagnoses [15], are graphed.”
Regulation of targeting determinants in interorganelle communication
Alli‐Balogun, G. O., & Levine, T. P. (2019) · Current Opinion in Cell Biology · doi:10.1016/j.ceb.2018.12.010 · Cited by 17
Paladin, L., Tosatto, S. C. E., & Minervini, G. (2015) · FEBS Letters · doi:10.1016/j.febslet.2015.11.022 · Cited by 17
“throughput affinity-purification mass spectrometry experiments [63]”
MethodProtein Analysis by Shotgun Proteomics
Gao, Y., & Yates, J. R. (2019) · Wiley eBooks · doi:10.1002/9781118970195.ch1 · Cited by 21
Unveiling the hidden interactome of CRBN molecular glues with chemoproteomicsPreprint
Baek, K., Metivier, R. J., Burman, S. S. R., Bushman, J. W., Yoon, H., Lumpkin, R. J., Abeja, D. M., Lakshminarayan, M., Yue, H., Ojeda, S., et al. (2024) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2024.09.11.612438 · Cited by 17
Functional analysis of cancer-associated germline risk variants
Kellman, L. N., Neela, P. H., Srinivasan, S., Siprashvili, Z., Shanderson, R. L., Hong, A. W., Rao, D. S., Porter, D. F., Reynolds, D. L., Meyers, R. M., et al. (2025) · Nature Genetics · doi:10.1038/s41588-024-02070-5 · Cited by 18
“Curating these with known protein–protein interactions 57,58 revealed ptGene networks associated with mitochondrial translation, DNA damage, RNA splicing and cell adhesion, as well as others (Extended Data Fig.”
The toll like receptor 7 pathway and the sex bias of systemic lupus erythematosus
Scofield, R. H., Wren, J. D., & Lewis, V. M. (2025) · Frontiers in Immunology · doi:10.3389/fimmu.2025.1479814 · Cited by 16
“As described above, the TASL gene routinely escapes X inactivation and TASL is expressed in several immune cells, including B lymphocytes and monocytes, contains an SLE risk allele (19, 35) and binds SLC15A4 on the lysosomal surface (44).”
Recent developments of sequence-based prediction of protein–protein interactions
Murakami, Y., & Mizuguchi, K. (2022) · Biophysical Reviews · doi:10.1007/s12551-022-01038-1 · Cited by 16
“APID (Agile Protein Interaction Data Analyzer) (Alonso-Lopez et al. 2019) provides a collection of known experimentally validated PPIs for more than 400 organisms from DIP (Sal-winski et al. 2004), IntAct, MINT, HPRD (Keshava Prasad et al. 2009), BioGRID, BioPlex (Huttlin et al. 2015), and also from experimentally res…”
BackgroundJin, X., Zhang, H., Wang, J., Li, J., Zhong, Y., Cao, X., Jin, J., Lin, Y., Ma, X., Yu, Z., et al. (2023) · Cell Death and Disease · doi:10.1038/s41419-023-05891-0 · Cited by 15
“Identification of INF2 as a novel FBXO7 interacting protein The affinity-purification mass spectrometry (AP-MS) result from two proteomics studies hint the potential interacted proteins of FBXO7 including INF2, a key factor in DRP1-associated mitochondrial division [21, 22].”
BackgroundSkinnider, M. A., Akinlaja, M. O., & Foster, L. J. (2023) · Nature Communications · doi:10.1038/s41467-023-44139-5 · Cited by 15
A network-based meta-analysis for characterizing the genetic landscape of human aging
Blankenburg, H., Pramstaller, P. P., & Domingues, F. S. (2017) · Biogerontology · doi:10.1007/s10522-017-9741-5 · Cited by 17
“BioPlex is an ongoing effort to unravel the landscape of all human protein complexes (Huttlin et al. 2015).”
BackgroundPortela, M., Yang, L., Paul, S., Li, X., Veraksa, A. N., Parsons, L. M., & Richardson, H. E. (2018) · Science Signaling · doi:10.1126/scisignal.aar1976 · Cited by 16
Decrypting protein surfaces by combining evolution, geometry, and molecular docking
Dequeker, C., Laine, É., & Carbone, A. (2019) · Proteins Structure Function and Bioinformatics · doi:10.1002/prot.25757 · Cited by 16
“Our knowledge 35 of protein-protein interaction (PPI) networks [2] is largely incomplete, since the experimental assessment of 36 all possible interactions of a protein is very challenging [3, 4].”
BackgroundThe True Story of Yeti, the “Abominable” Heterochromatic Gene of Drosophila melanogaster
Prozzillo, Y., Monache, F. D., Ferreri, D., Cuticone, S., Dimitri, P., & Messina, G. (2019) · Frontiers in Physiology · doi:10.3389/fphys.2019.01093 · Cited by 16
“Studies on the cp27 protein (later called mCFDP1) have shown specific interaction with NF-Y nuclear factor which bind CCAAT box (Luan et al., 2010; Ito et al., 2011), and with the TFII-I transcription factors involved in craniofacial development and osteo-differentiation Frontiers in Physiology |…”
BackgroundThareja, S. K., North, L. M., Stamm, K., Earing, M. G., Frommelt, M. A., Willes, R. J., Tripathi, S., Dsouza, N. R., Zimmermann, M. T., Mahnke, D. K., et al. (2020) · Molecular Genetics & Genomic Medicine · doi:10.1002/mgg3.1152 · Cited by 16
“The BioPlex database (Huttlin et al., 2015) identifies with 99% probability that KLHL26 interacts with Cullin-3 (CUL3), an important subunit of E3 ubiquitin ligase.”
BackgroundExperimental Approaches in Delineating mTOR Signaling
Qian, J., Su, S., & Liu, P. (2020) · Genes · doi:10.3390/genes11070738 · Cited by 17
“searched the BioPlex database (a human protein-protein interaction database [96]) for GATOR2 binding proteins and found GATSL3 (CASTOR1) as a GATOR2 binding partner, while GATSL2 (CASTOR2) interacted with GATOR1 [97].”
BackgroundOviya, R. P., Gopisetty, G., Jayavelu, S., & Rajkumar, T. (2021) · The Journal of Biochemistry · doi:10.1093/jb/mvab004 · Cited by 17
Rudashevskaya, E. L., Sickmann, A., & Markoutsa, S. (2016) · Expert Review of Proteomics · doi:10.1080/14789450.2016.1233064 · Cited by 15
Robinson, S., Nevalainen, J., Pinna, G., Campalans, A., Radicella, J. P., & Guyon, L. (2017) · Bioinformatics · doi:10.1093/bioinformatics/btx244 · Cited by 17
Direct Molecular Fishing of New Protein Partners for Human Thromboxane Synthase
Svirid, A. V., Ershov, P. V., Yablokov, E. O., Kaluzhskiy, L. A., Mezentsev, Y. V., Florinskaya, A. V., Sushko, T. A., Strushkevich, N. V., Strushkevich, N. V., Gilep, A. A., et al. (2017) · Acta Naturae · doi:10.32607/20758251-2017-9-4-92-100 · Cited by 18
Kornej, J., Buttner, P. G., Hammer, E., Engelmann, B., Dinov, B., Sommer, P., Husser, D., Hindricks, G., Völker, U., & Bollmann, A. (2018) · PLoS ONE · doi:10.1371/journal.pone.0198461 · Cited by 16
“Interestingly, an interaction of TTC39A with P2RY12, a receptor involved in platelet aggregation, regarded to be a potential target of thromboembolism treatment, was supposed [33].”
BackgroundChoi, S., Pfleger, J. M., Jeon, Y. H., Yang, Z., He, M., Shin, H., Sayed, D. H., Astrof, S., & Abdellatif, M. (2019) · Biochimica et Biophysica Acta (BBA) - Gene Regulatory Mechanisms · doi:10.1016/j.bbagrm.2019.194436 · Cited by 18
Lombard‐Banek, C., & Schiel, J. E. (2020) · Molecules · doi:10.3390/molecules25061396 · Cited by 16
“For example, PantherDB [66] and David [67] enable GO annotation based on protein/gene names, KEGG [68] or Ingenuity Pathway Analysis (Agilent) infer on gene set enrichment, and STRING [69] and recently BioPlex [70] can help build protein interaction networks.”
MethodGong, W., Guerler, A., Zhang, C., Warner, E., Li, C., & Zhang, Y. (2021) · Journal of Molecular Biology · doi:10.1016/j.jmb.2021.166944 · Cited by 13
Autophagy-independent role of ATG9A vesicles as carriers for galectin-9 secretion
Zhang, W., Ji, C., Li, X., He, T., Jiang, W., Liu, Y., Wu, M., Zhao, Y., Chen, X., Wang, X., et al. (2025) · Nature Communications · doi:10.1038/s41467-025-59605-5 · Cited by 16
Investigation and Prediction of Human Interactome Based on Quantitative Features
Pan, X., Zeng, T., Zhang, Y., Chen, L., Feng, K., Huang, T., & Cai, Y. (2020) · Frontiers in Bioengineering and Biotechnology · doi:10.3389/fbioe.2020.00730 · Cited by 15
“They were defined in three previous studies (Hein et al., 2015; Huttlin et al., 2015; Wan et al., 2015) and represented various biological characteristics of PPI.”
BackgroundMethodInfluentialBiotin Proximity Labeling for Protein–Protein Interaction Discovery: The BioID Method
Habel, J. E. (2021) · Methods in molecular biology · doi:10.1007/978-1-0716-1186-9_22 · Cited by 15
Yang, J., Peng, S., & Zhang, K. (2021) · Frontiers in Cell and Developmental Biology · doi:10.3389/fcell.2021.697831 · Cited by 15
Wei, X., Wang, B., Wu, Z., Yang, X., Guo, Y., Yang, Y., Fang, Z., Yi, C., Zhang, L., Fan, X., et al. (2023) · Cancer Letters · doi:10.1016/j.canlet.2023.216058 · Cited by 15
Godfroy, O., Zheng, M. H., Yao, H., Henschen, A., Peters, A. F., Scornet, D., Colin, S., Ronchi, P., Hipp, K., Nagasato, C., et al. (2023) · Development · doi:10.1242/dev.201283 · Cited by 16
Kovács, P., Pushparaj, P. N., Takács, R., Mobasheri, A., & Matta, C. (2023) · Frontiers in Immunology · doi:10.3389/fimmu.2023.1103097 · Cited by 15
“Clusterin binds to TNF-a in the BioPlex human interactome network (141).”
Dell’Amico, C., Salavarria, M. M. A., Takeo, Y., Saotome, I., Dell’Anno, M. T., Galimberti, M., Pellegrino, E., Cattaneo, E. F., Louvi, A., & Onorati, M. (2023) · eLife · doi:10.7554/elife.81716 · Cited by 16
Hypothesis: NDL proteins function in stress responses by regulating microtubule organization
Khatri, N., & Mudgil, Y. (2015) · Frontiers in Plant Science · doi:10.3389/fpls.2015.00947 · Cited by 15
“In plants, NDL proteins were first reported in sunflower (SF21) as stigma and transmitting tissue cell specific proteins (Kräuter-Canham et al., 1997).”
Backgroundp37/UBXN2B regulates spindle orientation by limiting cortical NuMA recruitment via PP1/Repo-Man
Lee, B. H., Schwager, F., Meraldi, P., & Gotta, M. (2017) · The Journal of Cell Biology · doi:10.1083/jcb.201707050 · Cited by 16
“This model is compatible with proteomic studies, which reported interactions between several PP1 subunits and p37 (Huttlin et al., 2015, 2017; Raman et al., 2015).”
ResultBansal, M., He, J., Peyton, M., Kustagi, M., Iyer, A., Comb, M. J., White, M. A., Minna, J. D., & Califano, A. (2019) · PLoS ONE · doi:10.1371/journal.pone.0208646 · Cited by 14
GOcats: A tool for categorizing Gene Ontology into subgraphs of user-defined concepts
Hinderer, E. W., & Moseley, H. (2020) · PLoS ONE · doi:10.1371/journal.pone.0233311 · Cited by 15
“4 interaction networks and form predictions of unknown protein function based on these networks (6,7), for gene annotation enrichment analyses, and are now being leveraged for the creation of predictive disease models in the scope of systems biochemistry (8).”
BackgroundSakaguchi, Y., Yoshihashi, H., Uehara, T., Miyama, S., Kosaki, K., & Takenouchi, T. (2020) · American Journal of Medical Genetics Part A · doi:10.1002/ajmg.a.62020 · Cited by 15
Sorokina, E. A., Reis, L. M., Thompson, S., Agre, K. E., Babovic‐Vuksanovic, D., Ellingson, M. S., Hasadsri, L., van Bever, Y., & Semina, E. V. (2021) · Human Genetics · doi:10.1007/s00439-021-02384-y · Cited by 15
Wang, Z., Li, M., Liu, Y., Qiao, Z., Yang, L., Liu, B., & Bai, T. (2022) · Cancer Gene Therapy · doi:10.1038/s41417-021-00423-4 · Cited by 16
“(2015) using affinity chromatography and anti-tag co-immunoprecipitation (co-IP) technologies showed that CRHBP may bind to p62 [14].”
BackgroundInfluentialProteomics profiling of interactome dynamics by colocalisation analysis (COLA)
Mardakheh, F. K., Sailem, H., Kuemper, S., Tape, C. J., McCully, R. R., Paul, A., Anjomani‐Virmouni, S., Jørgensen, C., Poulogiannis, G., Marshall, C. J., et al. (2016) · Molecular BioSystems · doi:10.1039/c6mb00701e · Cited by 15
Dong, S., Hu, W., Yang, T., Chen, X., Yan, H., Chen, X., Tan, L., Tian, Q., Deng, H., & Guo, Y. (2017) · Scientific Reports · doi:10.1038/srep43939 · Cited by 14
Identification and characterization of the BRI2 interactome in the brain
Martins, F., Marafona, A. M., Pereira, C. D., Müller, T., Looße, C., Kolbe, K., Silva, O. A. B. D. C. E., & Rebelo, S. (2018) · Scientific Reports · doi:10.1038/s41598-018-21453-3 · Cited by 15
McKenna, B. G., Koomar, T., Vervier, K., Kremsreiter, J. L., & Michaelson, J. J. (2018) · Molecular Case Studies · doi:10.1101/mcs.a003285 · Cited by 15
“Both of these transcription factors are highly expressed in the brain (Fagerberg et al. 2014) and involved in forming the AP1 transcription factor complex (Huttlin et al. 2015), which responds to cytokines and growth factor signaling.”
BackgroundPolesskaya, A., Boutillon, A., Yang, S., Wang, Y., Romero, S., Liu, Y., Lavielle, M., Molinié, N., Rocques, N., Fokin, A. I., et al. (2020) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2020.07.02.184655 · Cited by 17
“Both CYFIP proteins incorporate into WAVE complexes [44-46].”
BackgroundStructure of LRRK1 and mechanisms of autoinhibition and activation
(2023) · doi:10.1038/s41594-023-01109-1 · Cited by 15
“4a,b), and that no peptides for either LRRK1 or LRRK2 were found in the 293T cell proteome in a previous study 22 .”
BackgroundSubbanna, M. S., Winters, M. J., Örd, M., Davey, N. E., & Pryciak, P. M. (2025) · Journal of Biological Chemistry · doi:10.1016/j.jbc.2025.108225 · Cited by 16
Challenges and Opportunities for Bayesian Statistics in Proteomics
Crook, O. M., Chung, C., & Deane, C. M. (2022) · Journal of Proteome Research · doi:10.1021/acs.jproteome.1c00859 · Cited by 14
Rios, K. E., Zhou, M., Lott, N. M., Beauregard, C. R., McDaniel, D. P., Conrads, T. P., & Schaefer, B. C. (2022) · Cells · doi:10.3390/cells11071175 · Cited by 13
TREAT: Therapeutic RNAs exploration inspired by artificial intelligence technology
Luo, Y., Liu, L., He, Z., Zhang, S., Huo, P., Wang, Z., Jiaxin, Q., Zhao, L., Wu, Y., Zhang, D., et al. (2022) · Computational and Structural Biotechnology Journal · doi:10.1016/j.csbj.2022.10.011 · Cited by 14
“Coding gene-related relationships are from HURI [23], Bio-plex [26], PhosphoSitePlus [27], BioGRID [28], InnateDB [29], MINT [30], INSIDER [31], and DIP [32].”
MethodLiu, Z., Qian, W., Cai, W., Song, W., Wang, W., Maharjan, D. T., Cheng, W., Chen, J., Xu, F., Wang, H., et al. (2023) · Research · doi:10.34133/research.0219 · Cited by 16
Lu, X., Lu, J., Li, S., Feng, S., Wang, Y., & Cui, L. (2024) · Aging and Disease · doi:10.14336/ad.2024.0209 · Cited by 17
“Researchers have also attempted to use high-throughput, mass spectrometry-based methods to perform comprehensive analyses of protein‒protein interaction networks [169, 170] to identify the nucleolar proteome [171].”
Serrano, L. R., Pelin, A., Arrey, T. N., Damoc, N. E., Richards, A., Zhou, Y. M., Lancaster, N. M., Peters-Clarke, T. M., Pashkova, A., Jang, G. Μ., et al. (2025) · Journal of Proteome Research · doi:10.1021/acs.jproteome.4c01040 · Cited by 14
Import mechanism of peroxisomal proteins with an N-terminal signal sequence
Skowyra, M. L., & Rapoport, T. A. (2025) · Nature Cell Biology · doi:10.1038/s41556-025-01662-5 · Cited by 16
“A possible mechanism was suggested by large-scale protein-interaction studies in yeast 40,41 and mammalian cells 42–44 , which had identified an uncharacterized binding partner of PEX7 in the cytosol that has recently been named PEX39 (ref.”
Halu, A., Wang, J., Iwata, H., Mojcher, A., Abib, A. L., Singh, S. A., Aikawa, M., & Sharma, A. (2018) · eLife · doi:10.7554/elife.37059 · Cited by 12
“0 (http://bioplex.hms.harvard.edu/; Huttlin et al., 2015) contained 56,553 interactions and (Hein et al.”
BackgroundLi, H., Zhou, D., Chang, H., Wang, L., Liu, W., Dai, S., Zhang, C., Cai, J., Liu, W., Li, X., et al. (2019) · Journal of Psychiatric Research · doi:10.1016/j.jpsychires.2019.05.024 · Cited by 14
Explore Protein–Protein Interactions for Cancer Target Discovery Using the OncoPPi Portal
Ivanov, A. A. (2019) · Methods in molecular biology · doi:10.1007/978-1-4939-9873-9_12 · Cited by 14
Bon-Baret, V., Chignon, A., Boulanger, M., Li, Z., Argaud, D., Arsenault, B. J., Thériault, S., Bossé, Y., & Mathieu, P. (2021) · Circulation Genomic and Precision Medicine · doi:10.1161/circgen.120.003196 · Cited by 13
Discovery–Versus Hypothesis–Driven Detection of Protein–Protein Interactions and Complexes
Bludau, I. (2021) · International Journal of Molecular Sciences · doi:10.3390/ijms22094450 · Cited by 11
“, kinases [8]), and to even larger scale studies, such as the effort to map PPIs across all human ORFs [6,9,10].”
BackgroundInfluentialAxon-Specific Mitochondrial Pathology in SPG11 Alpha Motor Neurons
Güner, F., Pozner, T., Krach, F., Prots, I., Loskarn, S., Schlötzer-Schrehardt, U. M., Winkler, J., Winner, B., & Regensburger, M. (2021) · Frontiers in Neuroscience · doi:10.3389/fnins.2021.680572 · Cited by 14
Metabolic endophenotype associated with right ventricular glucose uptake in pulmonary hypertension
Farha, S., COMHAIR, S. A. A., Hou, Y., Park, M. M., Sharp, J., Peterson, L., Willard, B. B., Zhang, R., DiFilippo, F. P., Neumann, D. R., et al. (2021) · Pulmonary Circulation · doi:10.1177/20458940211054325 · Cited by 14
“0;(42) and (5) protein complexes data (56,000 candidate interactions) identified by a robust affinity purification-mass spectrometry methodology were collected from BioPlex V2.(43) The genes were mapped to their Entrez ID based on the NCBI database as well as their official gene symbols based on GeneCards (http://www.”
MethodSartori, G., Napoli, S., Cascione, L., Chung, E. Y., Priebe, V., Arribas, A. J., Mensah, A. A., Dall’Angelo, M., Falzarano, C., Barnabei, L., et al. (2021) · Journal of Experimental & Clinical Cancer Research · doi:10.1186/s13046-021-02159-3 · Cited by 17
Construction and contextualization approaches for protein-protein interaction networks
Badkas, A., Landtsheer, S. D., & Sauter, T. (2022) · Computational and Structural Biotechnology Journal · doi:10.1016/j.csbj.2022.06.040 · Cited by 14
“A database of cell-line specific networks, BioPLEX, is also under construction [27].”
BackgroundMclean, C. (2016) · Journal of Proteomics & Bioinformatics · doi:10.4172/jpb.1000383 · Cited by 14
“To test how our findings translate to other large proteome datasets we looked at the BioPlex network [17].”
BackgroundMethodInfluentialFitzsimmons, R., Amin, N. E., & Uversky, V. N. (2016) · Intrinsically Disordered Proteins · doi:10.1080/21690707.2016.1248273 · Cited by 14
Gene co-opening network deciphers gene functional relationships
Li, W., Wang, M., Sun, J., Wang, Y., & Jiang, R. (2017) · Molecular BioSystems · doi:10.1039/c7mb00430c · Cited by 14
The Notch Interactome: Complexity in Signaling Circuitry
Ho, D. M., Guruharsha, K. G., & Artavanis‐Tsakonas, S. (2018) · Advances in experimental medicine and biology · doi:10.1007/978-3-319-89512-3_7 · Cited by 14
Chen, J., & Kuhn, L. A. (2019) · Journal of Molecular Graphics and Modelling · doi:10.1016/j.jmgm.2019.04.003 · Cited by 15
“However, the binding of hSerpinB12 to RNA pol II [113] suggests an alternative role in RNA rather than DNA binding.”
BackgroundC20orf27 Promotes Cell Growth and Proliferation of Colorectal Cancer via the TGFβR-TAK1-NFĸB Pathway
Gao, J., Wang, Y., Zhang, W., Zhang, J., Lu, S., Meng, K., Yin, X., Sun, Z., & He, Q. (2020) · Cancers · doi:10.3390/cancers12020336 · Cited by 14
“According to the mass spectrometry results, the band is the catalytic subunit of serine threonine (PP1c) [8].”
BackgroundContribution of Mass Spectrometry-Based Proteomics to the Understanding of TNF-α Signaling
Ciuffa, R., Caron, É., Leitner, A., Uliana, F., Gstaiger, M., & Aebersold, R. H. (2016) · Journal of Proteome Research · doi:10.1021/acs.jproteome.6b00728 · Cited by 14
An Atlas of Protein-Protein Interactions Across Mammalian TissuesPreprint
Skinnider, M. A., Scott, N. E., Prudova, A., Stoynov, N., Stacey, R. G., Gsponer, J., & Foster, L. J. (2018) · SSRN Electronic Journal · doi:10.1101/351247 · Cited by 14
“To select a precision cutoff for further analysis, we compared each mouse tissue interactome to five recently published high-throughput human interactome maps (Hein et al., 2015; Huttlin et al., 2015; Huttlin et al., 2017; Rolland et al., 2014; Wan et al., 2015).”
BackgroundMethodInfluentialThe p140Cap adaptor protein as a molecular hub to block cancer aggressiveness
Salemme, V., Angelini, C., Chapelle, J., Centonze, G., Natalini, D., Morellato, A., Taverna, D., Turco, E., Ala, U., & Defilippi, P. (2020) · Cellular and Molecular Life Sciences · doi:10.1007/s00018-020-03666-w · Cited by 15
“p140Cap was also identified in the interactome of NUFIP1 (nuclear fragile X mental retardation protein-interacting protein) [40, 41], BCAS4 (breast carcinoma amplified sequence 4) [41], ESR2 (estrogen receptor 2) [42], from human samples.”
BackgroundHe, Z., Gao, K., Dong, L., Liu, L., Qu, X., Zou, Z., Wu, Y., Bu, D., Guo, J., & Zhao, Y. C. (2023) · Computational and Structural Biotechnology Journal · doi:10.1016/j.csbj.2023.02.005 · Cited by 13
“To realistically simulate the regulatory relationships of the human molecular network, we collected 11 high-quality molecular interaction databases, including HuRI [9], BioPlex [25], BioGRID [26], DIP [27], MINT [28], InnateDB [29], PhosphoSitePlus [30], INSIDER [31], KnockTF [7], IntAct [32], and TRRUST [33].”
BackgroundGraph databases in systems biology: a systematic review
Mazein, I., Rougny, A., Mazein, A., Henkel, R., Gütebier, L., Michaelis, L., Ostaszewski, M., Schneider, R., Satagopam, V., Jensen, L. J., et al. (2024) · Briefings in Bioinformatics · doi:10.1093/bib/bbae561 · Cited by 15
“Well-established PPI databases are broadly available (including [33–40]).”
Dou, L., Xu, Z., Xu, J., Zang, C., Su, C., Pieper, A. A., Leverenz, J. B., Wang, F., Zhu, X., Cummings, J. L., et al. (2025) · npj Parkinson s Disease · doi:10.1038/s41531-025-00870-y · Cited by 21
Nardone, C., Mintseris, J., He, D., Rutter, J. C., Ebert, B. L., Gygi, S. P., & Rapoport, T. A. (2025) · Nature Structural & Molecular Biology · doi:10.1038/s41594-025-01610-9 · Cited by 15
“Large-scale proteomics studies have reported that WDR7, DMXL1/2 and ROGDI coimmunoprecipitate with each other and with V-ATPase subunits 39,47,48 (Extended Data Fig.”
Translating molecular advances in Down syndrome and Fragile X syndrome into therapies
Faúndez, V., Toma, I. D., Bardoni, B., Bartesaghi, R., Nižetić, D., de la Torre, R., Kadosh, R. C., Hérault, Y., Dierssen, M., Potier, M., et al. (2018) · European Neuropsychopharmacology · doi:10.1016/j.euroneuro.2018.03.006 · Cited by 14
“The interactome was obtained from six published proteome-wide interactomes datasets (Shannon et al. , 2003; Camargo et al. , 2007; Warde-Farley et al. , 2010; Wang et al. , 2011; Havugimana et al. , 2012; Corominas et al. , 2014; Huttlin et al. , 2015; Wan et al. , 2015).”
Meneses‐Salas, E., García-Melero, A., Blanco‐Muñoz, P., Jose, J., Brenner, M.-S., Lu, A., Tebar, F., Grewal, T., Rentero, C., & Enrich, C. (2020) · Cells · doi:10.3390/cells9051152 · Cited by 13
“In support of this, direct protein–protein interactions of annexins with several LE/Lys proteins have been reported, including the two‐pore channel (TPC1/2) [26], NPC1 [27], or the vacuolar proton pump (ATPase H+ transporting VO subunit a2) [28].”
BackgroundKim, S. M., Cho, S. Y., Kim, M. W., Roh, S. R., Shin, H. S., Suh, Y. H., Geum, D., & Lee, M. A. (2020) · PubMed Central · doi:10.14348/molcells.2020.0071 · Cited by 13
“We selected eight genes involved in nervous system development: BAALC binder of MAP3K1 and KLF4 (BAALC) (Wang et al., 2005), calcium/calmodulin dependent protein kinase II inhibitor 1 (CAMK2N1) (Lucchesi et al., 2011; Saha et al., 2006), myosin light chain kinase (MYLK) (Li et al., 2016a), NMU (Kasper et al., 2016), C…”
InfluentialPredicting Functions of Uncharacterized Human Proteins: From Canonical to Proteoforms
Poverennaya, E. V., Kiseleva, O. I., Romanova, A., & Pyatnitskiy, M. A. (2020) · Genes · doi:10.3390/genes11060677 · Cited by 12
“Interactome database BioPlex [38,39] is a developing project on building a human interactome by sequential annotation of human genes using the affinity purification coupled with mass spectrometry approach (AP-MS, [59]).”
BackgroundMethodTissue Proteomic Approaches to Understand the Pathogenesis of Inflammatory Bowel Disease
Martin, M. B., Chaparro, M., & Gisbert, J. P. (2021) · Inflammatory Bowel Diseases · doi:10.1093/ibd/izaa352 · Cited by 13
Mitochondrially localized MPZL3 emerges as a signaling hub of mammalian physiology
Wikramanayake, T. C., Nicu, C., Chéret, J., Czyzyk, T. A., & Paus, R. (2021) · BioEssays · doi:10.1002/bies.202100126 · Cited by 13
Vanderwall, D., Poudel, S., Fu, Y., Cho, J., Shaw, T. I., Mishra, A., High, A. A., Peng, J., & Li, Y. (2021) · Journal of Visualized Experiments · doi:10.3791/62796 · Cited by 16
Herebian, D. A., Alhaddad, B., Seibt, A., Schwarzmayr, T., Danhauser, K., Klee, D., Harmsen, S., Meitinger, T., Strom, T. M., Schulz, A., et al. (2017) · European Journal of Human Genetics · doi:10.1038/ejhg.2017.96 · Cited by 13
Genevini, P., Colombo, M. N., Venditti, R., Marcuzzo, S., Colombo, S. F., Bernasconi, P., Matteis, M. A. D., Borgese, N., & Navone, F. (2019) · Journal of Cell Science · doi:10.1242/jcs.220061 · Cited by 15
“To be noted, the sets of binding partners ofVAPA and VAPB overlap to a large extent (Huttlin et al., 2015; Murphy and Levine, 2016), and specific roles that functionally distinguish the two VAP isoforms have not been identified yet.”
BackgroundInteger Linear Programming in Computational and Systems Biology: An Entry-Level Text and Course
Gusfield, D. (2019) · Cited by 13
Kong, Q., Huang, P., Chu, B., Ke, M., Chen, W., Zheng, Z., Ji, S., Cai, Z., Li, P., & Tian, R. (2020) · Analytical Chemistry · doi:10.1021/acs.analchem.0c00839 · Cited by 13
Pal, R. R., Kumar, A., & Misra, G. (2021) · Briefings in Bioinformatics · doi:10.1093/bib/bbab007 · Cited by 13
Tankyrase regulates epithelial lumen formation via suppression of Rab11 GEFs
Chandrakumar, A. A., Coyaud, É., Marshall, C. B., Ikura, M., Raught, B., & Rottapel, R. K. (2021) · The Journal of Cell Biology · doi:10.1083/jcb.202008037 · Cited by 13
“…be a novel Tankyrase substrate since it contains a conserved Tankyrase binding motif RxxxxG and was observed in several independent Tankyrase immuno-precipitation mass spectrometry experiments (Guettler et al., 2011; Wang et al., 2015; Li et al., 2017; Huttlin et al., 2015; Bhardwaj et al., 2017).”
BackgroundQuantitative proteomics of model organisms
Feng, Y., Cappelletti, V., & Picotti, P. (2017) · Current Opinion in Systems Biology · doi:10.1016/j.coisb.2017.09.004 · Cited by 12
Spatially resolved proteomics in osteoarthritis: State of the art and new perspectives.
Eveque-Mourroux, M., Rocha, B., Barré, F. P. Y., Heeren, R., & Cillero-Pastor, B. (2020) · Journal of Proteomics · doi:10.1016/j.jprot.2020.103637 · Cited by 12
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
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
