Cited by 1,392Bioinformatics and Genomic NetworksFungal and yeast genetics researchAdvanced Proteomics Techniques and Applications

The DOI matches its Crossref record; 46 of the 46 references it cites were found in a registry or an index.

High-Quality Binary Protein Interaction Map of the Yeast Interactome Network

Open access

Yu, Haiyuan, Braun, Pascal, Yıldırım, Muhammed A., Lemmens, Irma, Venkatesan, Kavitha, Sahalie, Julie, Hirozane-Kishikawa, Tomoko, Gebreab, Fana, Li, Na, Simonis, Nicolas, Hao, Tong, Rual, Jean-François, Dricot, Amélie, Vazquez, Alexei, Murray, Ryan R., Simon, Christophe, Tardivo, Leah, Tam, Stanley, Svrzikapa, Nenad, Fan, Changyu, de Smet, Anne-Sophie, Motyl, Adriana, Hudson, Michael E., Park, Juyong, Xin, Xiaofeng, Cusick, Michael E., Moore, Troy, Boone, Charlie, Snyder, Michael, Roth, Frederick P., Barabási, Albert-László, Tavernier, Jan, Hill, David E., Vidal, Marc·2008·Science

DOI 10.1126/science.1158684PMC PMC2746753

Open this paper in CoChat — free account

Abstract

Current yeast interactome network maps contain several hundred molecular complexes with limited and somewhat controversial representation of direct binary interactions. We carried out a comparative quality assessment of current yeast interactome data sets, demonstrating that high-throughput yeast two-hybrid (Y2H) screening provides high-quality binary interaction information. Because a large fraction of the yeast binary interactome remains to be mapped, we developed an empirically controlled mapping framework to produce a “second-generation” high-quality, high-throughput Y2H data set covering ∼20% of all yeast binary interactions. Both Y2H and affinity purification followed by mass spectrometry (AP/MS) data are of equally high quality but of a fundamentally different and complementary nature, resulting in networks with different topological and biological properties. Compared to co-complex interactome models, this binary map is enriched for transient signaling interactions and intercomplex connections with a highly significant clustering between essential proteins. Rather than correlating with essentiality, protein connectivity correlates with genetic pleiotropy.

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

Crossref · 10.1126/science.1158684

Cites

46 of 46 references verified0 citation errors · 0 not checkable

Statistics

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?

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Emergence of Scaling in Random Networks
Barabási, A.-L., & Albert, R. (1999) · Science · doi:10.1126/science.286.5439.509 · Cited by 36,135
Network motifs: simple building blocks of complex networks.
Milo, R., Shen-Orr, S., Itzkovitz, S., Kashtan, N., Chklovskii, D., & Alon, U. (2002) · Science · doi:10.1126/science.298.5594.824 · Cited by 7,368
Lethality and centrality in protein networks
Jeong, H., Mason, S., Barabási, A., & Oltvai, Z. (2001) · Nature · doi:10.1038/35075138 · Cited by 5,327
Functional 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
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
Systematic identification of protein complexes in Saccharomyces cerevisiae by mass spectrometry
Ho, Y., Gruhler, A., Heilbut, A. M., Bader, G. D., Moore, L., Adams, S., Millar, A., Taylor, P. P., Bennett, K. L., Boutilier, K., et al. (2002) · Nature · doi:10.1038/415180a · Cited by 3,573
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
Global landscape of protein complexes in the yeast Saccharomyces cerevisiae
Krogan, N. J., Cagney, G., Yu, H., Zhong, G., Guo, X., Ignatchenko, A., Li, J., Pu, S., Datta, N., Tikuisis, A., et al. (2006) · Nature · doi:10.1038/nature04670 · Cited by 2,964
Self-citation
Transcriptional Regulatory Networks in Saccharomyces cerevisiae
Lee, T. I., Rinaldi, N. J., Robert, F., Odom, D. T., Bar-Joseph, Z., Gerber, G. K., Hannett, N. M., Harbison, C. T., Thompson, C. M., Simon, I., et al. (2002) · Science · doi:10.1126/science.1075090 · Cited by 2,956
Towards a proteome-scale map of the human protein–protein interaction network
Rual, J.-F. M., Venkatesan, K., Hao, T., Hirozane-Kishikawa, T., Dricot, A., Li, N., Berriz, G. F., Gibbons, F. D., Dreze, M., Ayivi-Guedehoussou, N., et al. (2005) · Nature · doi:10.1038/nature04209 · Cited by 2,904
Self-citation

Flagged first, then by citations

Show all 45 references

Research works printed but not linked: 2

I. Remy, S. W. Michnick, Methods Mol. Biol.261, 411 (2004).
A. M. Dudley, D. M. Janse, A. Tanay, R. Shamir, G. M. Church, Mol. Syst. Biol.1, 0001 (2005).

Sorted by citations

Items 901–1,000 of 1,000

Mutual Information –The Biomarker of Essential Gene Predictions in Gene-Gene-Interaction of Lung Cancer
Payra, A. K., & Ghosh, A. (2019) · Communications in computer and information science · doi:10.1007/978-981-13-8581-0_19 · Cited by 9
Using discriminative vector machine model with 2DPCA to predict interactions among proteins
Li, Z., Nie, R., You, Z., Cao, C., & Li, J. (2019) · BMC Bioinformatics · doi:10.1186/s12859-019-3268-5 · Cited by 9
Predicted Drosophila Interactome Resource and web tool for functional interpretation of differentially expressed genes
Ding, X., Jin, J., Tao, Y., Guo, W., Ruan, L., Yang, Q., Chen, P., Yao, H., Zhang, H., & Chen, X. (2020) · Database · doi:10.1093/database/baaa005 · Cited by 9
Connectedness matters: construction and exact random sampling of connected networks
Horvát, S., & Modes, C. D. (2020) · Journal of Physics Complexity · doi:10.1088/2632-072x/abced5 · Cited by 12
Tah1, A Key Component of R2TP Complex that Regulates Assembly of snoRNP, is Involved in De Novo Generation and Maintenance of Yeast Prion [URE3]
Puri, A., Singh, P., Kumar, N., Kumar, R., & Sharma, D. (2021) · Journal of Molecular Biology · doi:10.1016/j.jmb.2021.166976 · Cited by 9
Trmt112 Gene Expression in Mouse Embryonic Development
Gu, T., He, H., Zhang, Y., Han, Z., Hou, G., Zeng, T.-B., Liu, Q., & Wu, Q. (2012) · ACTA HISTOCHEMICA ET CYTOCHEMICA · doi:10.1267/ahc.11047 · Cited by 9
Investigating the validity of current network analysis on static conglomerate networks by protein network stratification
Zhang, M., & Lu, L. J. (2010) · BMC Bioinformatics · doi:10.1186/1471-2105-11-466 · Cited by 9
Bioinformatics advances in protein ubiquitination
Liang, L. U., Li, D., & He, F. (2013) · Hereditas (Beijing) · doi:10.3724/sp.j.1005.2013.00017 · Cited by 10
A type 2 diabetes disease module with a high collective influence for Cdk2 and PTPLAD1 is localized in endosomes
Boutchueng-Djidjou, M., Belleau, P., Bilodeau, N., Fortier, S., Bourassa, S., Droit, A., Elowe, S., & Faure, R. L. (2018) · PLoS ONE · doi:10.1371/journal.pone.0205180 · Cited by 9
Methionine sulfoxide reductase 2 regulates Cvt autophagic pathway by altering the stability of Atg19 and Ape1 in Saccharomyces cerevisiae
Chatterjee, A., & Sepuri, N. B. V. (2024) · Journal of Biological Chemistry · doi:10.1016/j.jbc.2024.105662 · Cited by 8
The Analysis of the Power Law Feature in Complex Networks
Zhang, X., He, Z., Zhang, L., Rayman‐Bacchus, L., Shen, S., & Xiao, Y. (2022) · Entropy · doi:10.3390/e24111561 · Cited by 8
The protein interactome of the citrus Huanglongbing pathogen Candidatus Liberibacter asiaticus
Carter, E. W., Guerra‐Peraza, O., & Wang, N. (2023) · Nature Communications · doi:10.1038/s41467-023-43648-7 · Cited by 9
A comprehensive two-hybrid analysis to explore the Legionella pneumophila effector–effector interactome
Mount, H. O., Urbanus, M. L., Sheykhkarimli, D., Coté, A. G., Laval, F., Coppin, G., Kishore, N., Li, R., Spirohn, K., Petersen, M. O., et al. (2024) · mSystems · doi:10.1128/msystems.01004-24 · Cited by 8
Self-citation
Co-regulation of translation in protein complexes
Siwiak, M., & Zielenkiewicz, P. (2015) · Biology Direct · doi:10.1186/s13062-015-0048-7 · Cited by 8
Towards Personalized Medicine Mediated by in Vitro Virus-Based Interactome Approaches
Ohashi, H., & Miyamoto‐Sato, E. (2014) · International Journal of Molecular Sciences · doi:10.3390/ijms15046717 · Cited by 8
Deletion of Swm2p selectively impairs trimethylation of snRNAs by trimethylguanosine synthase (Tgs1p)
Boon, K.-L., & Koš, M. (2010) · FEBS Letters · doi:10.1016/j.febslet.2010.07.001 · Cited by 8
A Survey on Evolutionary Analysis in PPI Networks
Jancura, P., & Marchiori, E. (2012) · IntechOpen eBooks · doi:10.5772/37313 · Cited by 8
Binding interface change and cryptic variation in the evolution of protein-protein interactions
Ames, R. M., Talavera, D., Williams, S. G., Robertson, D. L., & Lovell, S. C. (2016) · BMC Evolutionary Biology · doi:10.1186/s12862-016-0608-1 · Cited by 8
A Mad2-Mediated Translational Regulatory Mechanism Promoting S-Phase Cyclin Synthesis Controls Origin Firing and Survival to Replication Stress
Gay, S., Piccini, D., Bruhn, C., Ricciardi, S., Soffientini, P., Carotenuto, W., Biffo, S., & Foiani, M. (2018) · Molecular Cell · doi:10.1016/j.molcel.2018.04.020 · Cited by 8
Controllability of Network: Identification of Controller Genes in a Gene–Gene Interaction Network
Payra, A. K., Ghosh, A., & Mitra, P. (2018) · Advances in intelligent systems and computing · doi:10.1007/978-981-13-1501-5_51 · Cited by 8
A Method for Improving the Accuracy of Link Prediction Algorithms
Li, J., Peng, X., Wang, J., & Zhao, N. (2021) · Complexity · doi:10.1155/2021/8889441 · Cited by 8
Prediction of Genes Involved in Lung Cancer with a Systems Biology Approach Based on Comprehensive Gene Information
Parvin, S., Sedighian, H., Sohrabi, E., Mahboobi, M., Rezaei, M., Ghasemi-Semeskandeh, D., & Rezaei, E. (2021) · Biochemical Genetics · doi:10.1007/s10528-021-10163-7 · Cited by 8
Embryonic Stem Cell Interactomics: The Beginning of a Long Road to Biological Function
Yousefi, M., Hajihoseini, V., Jung, W., Hosseinpour, B., Rassouli, H., Lee, B., Baharvand, H., Lee, K., & Salekdeh, G. H. (2012) · Stem Cell Reviews and Reports · doi:10.1007/s12015-012-9400-9 · Cited by 8
Network simulation reveals significant contribution of network motifs to the age-dependency of yeast protein–protein interaction networks
Liang, C., Luo, J., & Song, D. (2014) · Molecular BioSystems · doi:10.1039/c4mb00230j · Cited by 8
An in silico approach combined with in vivo experiments enables the identification of a new protein whose overexpression can compensate for specific respiratory defects in Saccharomyces cerevisiae
Glatigny, A., Mathieu, L., Herbert, C. J., Dujardin, G., Meunier, B., & Mucchielli-Giorgi, M.-H. (2011) · BMC Systems Biology · doi:10.1186/1752-0509-5-173 · Cited by 9
Dynamic Hubs Show Competitive and Static Hubs Non-Competitive Regulation of Their Interaction Partners
Goel, A., & Wilkins, M. R. (2012) · PLoS ONE · doi:10.1371/journal.pone.0048209 · Cited by 8
Genome-wide approaches to systematically identify substrates of the ubiquitin–proteasome pathway
Liu, C., Choe, V., & Rao, H. (2010) · Trends in biotechnology · doi:10.1016/j.tibtech.2010.06.003 · Cited by 8
Analysis of the Robustness of Degree Centrality against Random Errors in Graphs
Tsugawa, S., & Ohsaki, H. (2015) · Studies in computational intelligence · doi:10.1007/978-3-319-16112-9_3 · Cited by 8
Network Approaches to the Functional Analysis of Microbial Proteins
Hallinan, J. S., James, K., & Wipat, A. (2011) · Advances in microbial physiology/Advances in Microbial Physiology · doi:10.1016/b978-0-12-387661-4.00005-7 · Cited by 8
Mean field theory for biology inspired duplication-divergence network model
Cai, S., Liu, Z., & Lee, H. C. (2015) · Chaos An Interdisciplinary Journal of Nonlinear Science · doi:10.1063/1.4928212 · Cited by 8
A global protein–lipid interactome map
Brehme, M., & Vidal, M. (2010) · Molecular Systems Biology · doi:10.1038/msb.2010.100 · Cited by 8
Self-citation
Targeting and tinkering with interaction networks
Aloy, P. (2008) · FEBS Letters · doi:10.1016/j.febslet.2008.02.069 · Cited by 8
Modelling Biological Networks via Tailored Random Graphs
Coolen, A. C. C., Fraternali, F., Annibale, A., Fernandes, L. P., & Kleinjung, J. (2011) · Wiley eBooks · doi:10.1002/9781119970606.ch15 · Cited by 8
Mapping Technology Space by Normalizing Technology Relatedness Networks.Preprint
Alstott, J., Triulzi, G., Yan, B., & Luo, J. (2015) · arXiv (Cornell University) · Cited by 8
Optimal link prediction with matrix logistic regressionPreprint
Baldin, N., & Berthet, Q. (2018) · arXiv (Cornell University) · doi:10.48550/arxiv.1803.07054 · Cited by 8
Binary interactome models of inner- versus outer-complexome organisationPreprint
Lambourne, L., Yadav, A., Wang, Y., Desbuleux, A., Kim, D., Cafarelli, T. M., Pons, C., Kovács, I. A., Jailkhani, N., Schlabach, S., et al. (2021) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2021.03.16.435663 · Cited by 8
Self-citation
FlyPredictome: A structural atlas of predicted protein-protein interactions in DrosophilaPreprint
Kim, A., Comjean, A., Veal, A., Rodiger, J., Han, M., Hu, Y., & Perrimon, N. (2026) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2026.04.14.718529 · Cited by 11
Internetwork connectivity of molecular networks across species of life
Mahajan, T., & Dar, R. D. (2021) · Scientific Reports · doi:10.1038/s41598-020-80745-9 · Cited by 8
The transcriptional activator Pog1 controls cell cycle, and its phosphorylated form is downregulated by the ubiquitin ligase Dma2 inSaccharomyces cerevisiae
Oshiro, S., & Takagi, H. (2014) · FEMS Yeast Research · doi:10.1111/1567-1364.12190 · Cited by 7
When peptides fly: Advances in Drosophila proteomics
Veraksa, A. N. (2010) · Journal of Proteomics · doi:10.1016/j.jprot.2010.05.006 · Cited by 7
Molecular recognition at protein surface in solution and gas phase: Five VEGF peptidic ligands show inverse affinity when studied by NMR and CID‐MS
Dyachenko, A., Goldflam, M., Vilaseca, M., & Giralt, E. (2010) · Biopolymers · doi:10.1002/bip.21462 · Cited by 7
Quantifying the Effect of Community Structures for Link Prediction by Constructing Null Models
Xu, X.-K., Shang, K.-K., & Xiao, J. (2020) · IEEE Access · doi:10.1109/access.2020.2993455 · Cited by 7
A framework combines supervised learning and dense subgraphs discovery to predict protein complexes
Mei, S. (2021) · Frontiers of Computer Science · doi:10.1007/s11704-021-0476-8 · Cited by 7
Barcode fusion genetics-protein-fragment complementation assay (BFG-PCA): tools and resources that expand the potential for binary protein interaction discovery
(2022) · doi:10.1093/nar/gkac045 · Cited by 7
Gene transferability and sociality do not correlate with gene connectivity
Hao, C., Dewar, A. E., West, S. A., & Ghoul, M. (2022) · Proceedings of the Royal Society B Biological Sciences · doi:10.1098/rspb.2022.1819 · Cited by 6
A Novel Link Prediction Framework Based on Gravitational Field
Yang, Y., Ye, Z., Zhao, H., & Meng, L. (2023) · Data Science and Engineering · doi:10.1007/s41019-022-00201-8 · Cited by 7
Algorithmic Tools for Understanding the Motif Structure of Networks
Chen, T., Matejek, B., Mitzenmacher, M., & Tsourakakis, C. E. (2023) · Lecture notes in computer science · doi:10.1007/978-3-031-26390-3_1 · Cited by 7
Analysis of Protein Interaction Networks to Prioritize Drug Targets of Neglected-Diseases Pathogens
Segura‐Cabrera, A., Carlos, A., Mario, A., Guo, X., Rivera, G., & Bocanegra-Garc, V. (2012) · InTech eBooks · doi:10.5772/38463 · Cited by 7
Modes of Interaction between Individuals Dominate the Topologies of Real World Networks
Lee, I., Kim, E., & Marcotte, E. M. (2015) · PLoS ONE · doi:10.1371/journal.pone.0121248 · Cited by 8
The Bait Compatibility Index: Computational Bait Selection for Interaction Proteomics Experiments
Saha, S., Kaur, P., & Ewing, R. M. (2010) · Journal of Proteome Research · doi:10.1021/pr100267t · Cited by 7
Random Phenotypic Variation of Yeast (Saccharomyces cerevisiae) Single-Gene Knockouts Fits a Double Pareto-Lognormal Distribution
Graham, J. H., Robb, D. T., & Poe, A. R. (2012) · PLoS ONE · doi:10.1371/journal.pone.0048964 · Cited by 7
Energy Fluctuations Shape Free Energy of Nonspecific Biomolecular Interactions
Elkin, M., André, I., & Lukatsky, D. B. (2012) · Journal of Statistical Physics · doi:10.1007/s10955-012-0421-1 · Cited by 7
Belief Propagation Estimation of Protein and Domain Interactions Using the Sum–Product Algorithm
Morcos, F., Sikora, M., Alber, M., Kaiser, D., & Izaguirre, J. A. (2010) · IEEE Transactions on Information Theory · doi:10.1109/tit.2009.2037051 · Cited by 7
Incorporating communities’ structures in predictions of missing links
Yadav, R. K., & Rai, A. K. (2020) · Journal of Intelligent Information Systems · doi:10.1007/s10844-020-00603-y · Cited by 7
The Evolution of Protein Interaction Networks
Schüler, A., & Bornberg‐Bauer, E. (2010) · Methods in molecular biology · doi:10.1007/978-1-60761-987-1_17 · Cited by 7
Molecular Systems Biology of Sic1 in Yeast Cell Cycle Regulation Through Multiscale Modeling
Barberis, M. (2011) · Advances in experimental medicine and biology · doi:10.1007/978-1-4419-7210-1_7 · Cited by 7
Functional network motifs defined through integration of protein-protein and genetic interactions
Sahoo, A., & Pechmann, S. (2022) · PeerJ · doi:10.7717/peerj.13016 · Cited by 8
Revealing how network structure affects accuracy of link prediction
Yang, J.-X., & Zhang, X. (2017) · The European Physical Journal B · doi:10.1140/epjb/e2017-70599-4 · Cited by 7
Systems-Level Analysis of Bacterial Regulatory Small RNA Networks
Wong, J. L., Pang, C. N. I., Wilkins, M. R., & Tree, J. J. (2018) · RNA technologies · doi:10.1007/978-3-319-92967-5_6 · Cited by 7
Interactome and Gene Ontology provide congruent yet subtly different views of a eukaryotic cell
Marco, A. D., & Marı́n, I. (2009) · BMC Systems Biology · doi:10.1186/1752-0509-3-69 · Cited by 7
Poly(arginine)‐Selective Coprecipitation Properties of Self‐Assembling Apoferritin and Its Tb3+ Complex: A New Luminescent Biotool for Sensing of Poly(arginine) and Its Protein Conjugates
Tsukube, H., Noda, Y., & Shinoda, S. (2010) · Chemistry - A European Journal · doi:10.1002/chem.200902833 · Cited by 7
Know your limits: Assumptions, constraints and interpretation in systems biology
Ilsley, G. R., Luscombe, N. M., & Apweiler, R. (2009) · Biochimica et Biophysica Acta (BBA) - Proteins and Proteomics · doi:10.1016/j.bbapap.2009.05.002 · Cited by 7
Identifying Responsive Modules by Mathematical Programming: An Application to Budding Yeast Cell Cycle
Wen, Z., Liu, Z.-P., Yan, Y., Piao, G., Liu, Z., Wu, J., & Chen, L. (2012) · PLoS ONE · doi:10.1371/journal.pone.0041854 · Cited by 7
Accuracy improvement in protein complex prediction from protein interaction networks by refining cluster overlaps
Chiam, T. C., & Cho, Y. (2012) · Proteome Science · doi:10.1186/1477-5956-10-s1-s3 · Cited by 7
Network-Based Analysis for Biological Discovery
Tripathi, L. P., Chen, Y. A., Mizuguchi, K., & Murakami, Y. (2018) · Elsevier eBooks · doi:10.1016/b978-0-12-809633-8.20674-2 · Cited by 7
Bioinformatics prediction and screening of viral mimicry candidates through integrating known and predicted DMI data
Idrees, S., & Paudel, K. R. (2023) · Archives of Microbiology · doi:10.1007/s00203-023-03764-w · Cited by 6
Reverse-engineering of biochemical reaction networks from spatio-temporal correlations of fluorescence fluctuations
Tanaka, N., & Papoian, G. A. (2010) · Journal of Theoretical Biology · doi:10.1016/j.jtbi.2010.02.022 · Cited by 6
Gene duplications contribute to the overrepresentation of interactions between proteins of a similar age
Fokkens, L., Hogeweg, P., & Snel, ‎. (2012) · BMC Evolutionary Biology · doi:10.1186/1471-2148-12-99 · Cited by 6
Statistical and Computational Rates in Graph Logistic Regression
Berthet, Q., & Baldin, N. (2020) · International Conference on Artificial Intelligence and Statistics · Cited by 6
Bil2 Is a Novel Inhibitor of the Yeast Formin Bnr1 Required for Proper Actin Cable Organization and Polarized Secretion
Rands, T. J., & Goode, B. L. (2021) · Frontiers in Cell and Developmental Biology · doi:10.3389/fcell.2021.634587 · Cited by 6
Domination based classification algorithms for the controllability analysis of biological interaction networks
Grady, S. K., Abu-Khzam, F. N., Hagan, R. D., Shams, H., & Langston, M. A. (2022) · Scientific Reports · doi:10.1038/s41598-022-15464-4 · Cited by 6
Network Comparison with Interpretable Contrastive Network Representation Learning
Fujiwara, T., Zhao, J. F., Chen, F., Yu, Y., & Ma, K. (2022) · Journal of Data Science Statistics and Visualisation · doi:10.52933/jdssv.v2i5.56 · Cited by 9
Random search immune algorithm for community detection
Spampinato, A. G., Scollo, R. A., Cutello, V., & Pavone, M. F. (2023) · Soft Computing · doi:10.1007/s00500-023-07999-z · Cited by 6
A positive statistical benchmark to assess network agreement
Hao, B., & Kovács, I. A. (2023) · Nature Communications · doi:10.1038/s41467-023-38625-z · Cited by 6
An information-theoretic classification of amino acids for the assessment of interfaces in protein–protein docking
Jardin, C., Stefani, A. G., Eberhardt, M., Huber, J. B., & Sticht, H. (2013) · Journal of Molecular Modeling · doi:10.1007/s00894-013-1916-7 · Cited by 6
A random walk based approach for improving protein-protein interaction network and protein complex prediction
Lei, C., & Ruan, J. (2012) · IEEE International Conference on Bioinformatics and Biomedicine (BIBM) · doi:10.1109/bibm.2012.6392693 · Cited by 6
Limitations of Gene Duplication Models: Evolution of Modules in Protein Interaction Networks
Emmert‐Streib, F. (2012) · PLoS ONE · doi:10.1371/journal.pone.0035531 · Cited by 6
In-Frame cDNA Library Combined with Protein Complementation Assay Identifies ARL11-Binding Partners
Lee, S., Lee, I., Jung, Y., McConkey, D. J., & Czerniak, B. A. (2012) · PLoS ONE · doi:10.1371/journal.pone.0052290 · Cited by 6
Derivation of an interaction/regulation network describing pluripotency in human
Som, A., Luštrek, M., Singh, N. K., & Fuellen, G. (2012) · Gene · doi:10.1016/j.gene.2012.04.025 · Cited by 6
Protein Kinase C Epsilon and Genetic Networks in Osteosarcoma Metastasis
Goudarzi, A., Gökgöz, N., Gill, M., Pinnaduwage, D., Merico, D., Wunder, J. S., & Andrulis, I. L. (2013) · Cancers · doi:10.3390/cancers5020372 · Cited by 6
Coevolution is a short‐distance force at the protein interaction level and correlates with the modular organization of protein networks
Liang, Z. G., Xu, M., Teng, M., Niu, L., & Wu, J. (2010) · FEBS Letters · doi:10.1016/j.febslet.2010.09.014 · Cited by 6
High-Throughput Analyses and Curation of Protein Interactions in Yeast
Wodak, S. J., Vlasblom, J., & Pu, S. (2011) · Methods in molecular biology · doi:10.1007/978-1-61779-173-4_22 · Cited by 6
Modeling and simulating networks of interdependent protein interactions
Stöcker, B. K., Köster, J., Zamir, E., & Rahmann, S. (2018) · Integrative Biology · doi:10.1039/c8ib00012c · Cited by 6
Unit Disk Graph‐Based Node Similarity Index for Complex Network Analysis
Meghanathan, N. (2019) · Complexity · doi:10.1155/2019/6871874 · Cited by 6
Constrained Covariance Matrices With a Biologically Realistic Structure: Comparison of Methods for Generating High-Dimensional Gaussian Graphical Models
Emmert‐Streib, F., Tripathi, S., & Dehmer, M. (2019) · Frontiers in Applied Mathematics and Statistics · doi:10.3389/fams.2019.00017 · Cited by 6
A new grid- and modularity-based layout algorithm for complex biological networks
He, S., Liu, Y., Ye, F., Li, R., & Ren-jun, D. (2019) · PLoS ONE · doi:10.1371/journal.pone.0221620 · Cited by 6
A three-phase method for identifying functionally related protein groups in weighted PPI networks
Grbić, M., Matić, D., Kartelj, A., Vračević, S., & Filipović, V. (2020) · Computational Biology and Chemistry · doi:10.1016/j.compbiolchem.2020.107246 · Cited by 6
Topological ranks reveal functional knowledge encoded in biological networks: a comparative analysis
Bonomo, M., Giancarlo, R., Greco, D., & Rombo, S. E. (2022) · Briefings in Bioinformatics · doi:10.1093/bib/bbac101 · Cited by 6
Network reconstruction for trans acting genetic loci using multi-omics data and prior information
Hawe, J. S., Saha, A., Waldenberger, M., Kunze, S., Wahl, S., Müller‐Nurasyid, M., Prokisch, H., Grallert, H., Herder, C., Peters, A., et al. (2022) · Genome Medicine · doi:10.1186/s13073-022-01124-9 · Cited by 6
Population perspectives on functional genomic variation in yeast
Skelly, D. A., & Magwene, P. M. (2015) · Briefings in Functional Genomics · doi:10.1093/bfgp/elv044 · Cited by 6
Methods to Study Transcription Factor Structure and Function
Viola, I. L., & González, D. H. (2015) · Elsevier eBooks · doi:10.1016/b978-0-12-800854-6.00002-6 · Cited by 6
Networks in nature: dynamics, evolution, and modularity
Agarwal, S. (2012) · Oxford University Research Archive (ORA) (University of Oxford) · doi:10.5287/ora-xr1x2v5o5 · Cited by 6
Androgen receptor plays critical role in regulating cervical cancer cell migration
Bose, S., Das, S., Maity, S., Raychaudhuri, D., Banerjee, T., Paul, M., Mukhopadhyay, A., Chakrabarti, O., & Chakrabarti, S. (2025) · Molecular and Cellular Endocrinology · doi:10.1016/j.mce.2025.112583 · Cited by 5
Experimental assessment of AI-based interactome mapping
Lambourne, L., Yadav, A., Wang, Y., Desbuleux, A., Kim, D.-K., Laval, F., Spirohn, K., Cafarelli, T. M., Pons, C., Kovács, I. A., et al. (2026) · Nature Communications · doi:10.1038/s41467-026-70942-x · Cited by 6
Self-citation
Detection of Protein–Protein Interactions Utilizing the Split-Ubiquitin Membrane-Based Yeast Two-Hybrid System
Dutta, S., & Smith, M. D. (2023) · Methods in molecular biology · doi:10.1007/978-1-0716-3327-4_4 · Cited by 5
Accurate and sensitive interactome profiling using a quantitative protein-fragment complementation assay
Lazarewicz, N., Dez, G. L., Cerjani, R., Runeshaw, L., Meurer, M., Knop, M., Wysocki, R., & Rabut, G. E. E. (2024) · Cell Reports Methods · doi:10.1016/j.crmeth.2024.100880 · Cited by 5
The Whi2-Psr1-Psr2 complex selectively regulates TORC1 and autophagy under low leucine conditions but not nitrogen depletion
Wang, Y., Ping, Y., Zhou, R., Wang, G., Zhang, Y., Yang, X., Zhao, M., Liu, D., Kulkarni, M., Lamb, H., et al. (2025) · Autophagy · doi:10.1080/15548627.2025.2481014 · Cited by 5
FlyPhoneDB2: A computational framework for analyzing cell-cell communication in Drosophila scRNA-seq data integrating AlphaFold-multimer predictions
Qadiri, M., Liu, Y., Kim, A., Han, M., Zhou, E., Veal, A., Lu, T., Li, H., Hu, Y., & Perrimon, N. (2025) · Computational and Structural Biotechnology Journal · doi:10.1016/j.csbj.2025.06.032 · Cited by 5
Accurate and fast link prediction in complex networks
Zhang, W., Wu, B., & Zhang, W. (2014) · International Conference on Natural Computation (ICNC) · doi:10.1109/icnc.2014.6975913 · Cited by 5
Quality Control Methodology for High-Throughput Protein–Protein Interaction Screening
Vázquez, A., Rual, J.-F. M., & Venkatesan, K. (2011) · Methods in molecular biology · doi:10.1007/978-1-61779-276-2_13 · Cited by 5
Self-citation

Authors: Yu, H., Braun, P., Yıldırım, M. A., Lemmens, I., Venkatesan, K., Sahalie, J., Hirozane-Kishikawa, T., Gebreab, F., Li, N., Simonis, N., Hao, T., Rual, J.-F., Dricot, A., Vazquez, A., Murray, R. R., Simon, C., Tardivo, L., Tam, S., Svrzikapa, N., Fan, C., de Smet, A.-S., Motyl, A., Hudson, M. E., Park, J., Xin, X., Cusick, M. E., Moore, T., Boone, C., Snyder, M., Roth, F. P., Barabási, A.-L., Tavernier, J., Hill, D. E., & Vidal, M.
Affiliations: Harvard University (US)
Center for Cancer Systems Biology (CCSB), Dana-Farber Cancer Institute, Boston, MA 02115, USA.
Northeastern University (US)
Corresponding author: Yu, Haiyuan
Yıldırım, Muhammed A.
Vidal, Marc
ORCID: Yu, Haiyuan
Yıldırım, Muhammed A.
Lemmens, Irma
Venkatesan, Kavitha
Li, Na
Simonis, Nicolas
Hao, Tong
Tam, Stanley
Svrzikapa, Nenad
Park, Juyong
Xin, Xiaofeng
Snyder, Michael
Roth, Frederick P.
Tavernier, Jan
Hill, David E.
Vidal, Marc
Venue: Science
Publisher: American Association for the Advancement of Science (AAAS)
Published: 2008-10-03
Volume: 322
Issue: 5898
Pages: 104-110
ISSN: 0036-8075 (ISSN-L)
1095-9203
DOI: 10.1126/science.1158684
PMC: PMC2746753
OpenAlex: W2109248504
Cited by: 1,392
References: 45
Citations by year: 2026: 18 · 2025: 26 · 2024: 29 · 2023: 34 · 2022: 63 · 2021: 55 · 2020: 66 · 2019: 65 · 2018: 67 · 2017: 72 · 2016: 68 · 2015: 78 · 2014: 79 · 2013: 122 · 2012: 172
FWCI: 51.78
Type: journal article
Language: en
Open access: green
www.ncbi.nlm.nih.gov
Locations: Science (publishedVersion)
PubMed (publishedVersion)
PubMed Central (acceptedVersion)
Ghent University Academic Bibliography (Ghent University) (submittedVersion)
Dépôt institutionnel de l'Université libre de Bruxelles (Université Libre de Bruxelles) (submittedVersion, other-oa)
Funders: U.S. Public Health Service (U01A1070499-01)
National Human Genome Research Institute (R01HG001715, R01HG003224, HG003224)
National Cancer Institute (U56CA113004)
National Institute of Allergy and Infectious Diseases (U01AI070499)
Topics: Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bioinformatics and Genomic Networks
Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Fungal and yeast genetics research
Physical Sciences › Chemistry › Spectroscopy › Advanced Proteomics Techniques and Applications
Keywords: yeast interactome, protein-protein interaction network, yeast two-hybrid screening, affinity purification mass spectrometry, protein complexes, essential proteins, protein connectivity, pleiotropy, network topology
MeSH terms: Protein Binding, Saccharomyces cerevisiae, Mass Spectrometry, Transcription Factors, Signal Transduction, Computational Biology, Proteome, Two-Hybrid System Techniques, Protein Interaction Mapping, Saccharomyces cerevisiae Proteins, Protein Array Analysis, Proteomics, Gene Regulatory Networks, Metabolic Networks and Pathways

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

High-Quality Binary Protein Interaction Map of the Yeast Interactome Network

Abstract

Overview

Integrity signals

Verification

Claims the paper makes

Claims other papers make about this one

Self-check

Citations

Cites

Cited by

Related

Metadata

Record

About these checks