The DOI matches its Crossref record; 16 of the 17 references it cites were found in a registry or an index.
Guilt-by-association goes global
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
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?
In the citing paper
“GBA states that genes with similar functional properties will tend to interact or exhibit similar profiles in network data, such as co-expression.”
From Guidance for RNA-seq co-expression network construction and analysis: safety in numbers (2015) · cites this paper as Oliver, 2000
Citations
Cites
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
Goffeau, A., Barrell, B. G., Bussey, H., Davis, R. W., Dujon, B., Feldmann, H., Galibert, F., Hoheisel, J. D., Jacq, C., Johnston, M., et al. (1996) · Science · doi:10.1126/science.274.5287.546 · Cited by 4,423
Self-citationDirect analysis of protein complexes using mass spectrometry
Link, A. J., Eng, J. K., Schieltz, D. M., Carmack, E., Mize, G. J., Morris, D. R., Garvik, B. M., & Yates, J. R. (1999) · Nature Biotechnology · doi:10.1038/10890 · Cited by 2,218
Shevchenko, A., Jensen, O. N., Podtelejnikov, A. V., Sagliocco, F. A., Wilm, M. S., Vorm, O., Mortensen, P. M., Shevchenko, A., Boucherie, H., & Mann, M. (1996) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.93.25.14440 · Cited by 1,429
Systematic functional analysis of the yeast genome
Oliver, S. G. (1998) · Trends in biotechnology · doi:10.1016/s0167-7799(98)01214-1 · Cited by 1,374
Self-citationCharacterization of the Yeast Transcriptome
Velculescu, V. E., Zhang, L., Zhou, W., Vogelstein, R. J., Basrai, M. A., Bassett, D. E., Hieter, P., Vogelstein, B., & Kinzler, K. W. (1997) · Cell · doi:10.1016/s0092-8674(00)81845-0 · Cited by 973
Toward a functional analysis of the yeast genome through exhaustive two-hybrid screens
Fromont‐Racine, M., Rain, J., & Legrain, P. (1997) · Nature Genetics · doi:10.1038/ng0797-277 · Cited by 930
Characterization of Sm‐like proteins in yeast and their association with U6 snRNA
Mayes, A. E., Verdone, L., Legrain, P., & Beggs, J. D. (1999) · The EMBO Journal · doi:10.1093/emboj/18.15.4321 · Cited by 239
A protein–protein interaction map of yeast RNA polymerase III
Flores, A., Briand, J.-F., Gadal, O., Andrau, J., Rubbi, L., Mullem, V. V., Boschiero, C., Goussot, M., Marck, C., Carles, C., et al. (1999) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.96.14.7815 · Cited by 142
Hoheisel, J. D. (1997) · Trends in biotechnology · doi:10.1016/s0167-7799(97)01123-2 · Cited by 70
Flagged first, then by citations
1 of the 17 references couldn’t be matched to a known paper.
Cited by
Sorted by citations
Comparative assessment of large-scale data sets of protein–protein interactions
von Mering, C., Krause, R., Snel, ., Cornell, M. J., Oliver, S. G., Fields, S., & Peer Bork, B. (2002) · Nature · doi:10.1038/nature750 · Cited by 2,339
Self-citationDeep learning: new computational modelling techniques for genomics
Eraslan, G., Avsec, Ž., Gagneur, J., & Theis, F. J. (2019) · Nature Reviews Genetics · doi:10.1038/s41576-019-0122-6 · Cited by 1,270
A functional genomics strategy that uses metabolome data to reveal the phenotype of silent mutations
Raamsdonk, L. M., Teusink, B., Broadhurst, D., Zhang, N., Hayes, A., Walsh, M. C., BERDEN, J. A., Brindle, K. M., Kell, D. B., Rowland, J. J., et al. (2001) · Nature Biotechnology · doi:10.1038/83496 · Cited by 1,021
Self-citationA Census of Human Soluble Protein Complexes
Havugimana, P. C., Hart, T., Nepusz, T., Yang, H., Turinsky, A. L., Li, Z., Wang, P. I., Boutz, D. R., Fong, V., Phanse, S., et al. (2012) · Cell · doi:10.1016/j.cell.2012.08.011 · Cited by 869
Modular organization of cellular networks
Rives, A. W., & Galitski, T. (2003) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0237338100 · Cited by 705
Tong, A. H. Y., Drees, B., Nardelli, G., Bader, G. D., Brannetti, B., Castagnoli, L., Evangelista, M., Ferracuti, S., Nelson, B., Paoluzi, S., et al. (2002) · Science · doi:10.1126/science.1064987 · Cited by 692
Kaji, H., Saito, H., Yamauchi, Y., Shinkawa, T., Taoka, M., Hirabayashi, J., Kasai, K., Takahashi, N., & Isobe, T. (2003) · Nature Biotechnology · doi:10.1038/nbt829 · Cited by 612
High-throughput classification of yeast mutants for functional genomics using metabolic footprinting
Allen, J., Davey, H. M., Broadhurst, D., Heald, J. K., Rowland, J. J., Oliver, S. G., & Kell, D. B. (2003) · Nature Biotechnology · doi:10.1038/nbt823 · Cited by 538
Self-citationGenetic Basis of Mitochondrial Function and Morphology in Saccharomyces cerevisiae
Dimmer, K. S., Fritz, S., Fuchs, F., Messerschmitt, M., Weinbach, N., Neupert, W., & Westermann, B. (2002) · Molecular Biology of the Cell · doi:10.1091/mbc.01-12-0588 · Cited by 443
Artificial intelligence in cancer target identification and drug discovery
You, Y., Lai, X., Pan, Y. F., Zheng, H., Vera, J., Liu, S., Deng, S., & Zhang, L. (2022) · Signal Transduction and Targeted Therapy · doi:10.1038/s41392-022-00994-0 · Cited by 499
Interactome: gateway into systems biology
Cusick, M. E., Klitgord, N., Vidal, M., & HILL, D. E. (2005) · Human Molecular Genetics · doi:10.1093/hmg/ddi335 · Cited by 411
Three-dimensional reconstruction of protein networks provides insight into human genetic disease
Wang, X., Wei, X., Thijssen, B., Das, J., Lipkin, S. M., & Yu, H. (2012) · Nature Biotechnology · doi:10.1038/nbt.2106 · Cited by 385
Mitochondrial dynamics and division in budding yeast
Shaw, J. M., & Nunnari, J. (2002) · Trends in Cell Biology · doi:10.1016/s0962-8924(01)02246-2 · Cited by 375
Tieu, Q., & Nunnari, J. M. (2000) · The Journal of Cell Biology · doi:10.1083/jcb.151.2.353 · Cited by 375
History of protein–protein interactions: From egg‐white to complex networks
Falter‐Braun, P., & Gingras, A. (2012) · PROTEOMICS · doi:10.1002/pmic.201100563 · Cited by 328
Tanida, I., Tanida-Miyake, E., Komatsu, M., Ueno, T., & Kominami, E. (2002) · Journal of Biological Chemistry · doi:10.1074/jbc.m200385200 · Cited by 286
Deep learning for inferring gene relationships from single-cell expression data
Yuan, Y., & Bar‐Joseph, Z. (2019) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1911536116 · Cited by 270
Chiu, H., Somvanshi, S., Patel, E., Chen, T.-W., Singh, V., Zorman, B., Patil, S. L., Pan, Y., Chatterjee, S. S., Johnson, R., et al. (2018) · Cell Reports · doi:10.1016/j.celrep.2018.03.064 · Cited by 251
Guidance for RNA-seq co-expression network construction and analysis: safety in numbers
Ballouz, S., Verleyen, W., & Gillis, J. (2015) · Bioinformatics · doi:10.1093/bioinformatics/btv118 · Cited by 215
A systematic approach to modeling, capturing, and disseminating proteomics experimental data
Taylor, C. F., Paton, N. W., Garwood, K. L., Kirby, P. D., Stead, D., Yin, Z., Deutsch, E. W., Selway, L., Walker, J., Riba‐Garcia, I., et al. (2003) · Nature Biotechnology · doi:10.1038/nbt0303-247 · Cited by 248
Self-citationNetwork-based methods for human disease gene prediction
Wang, X., Gulbahce, N., & Yu, H. (2011) · Briefings in Functional Genomics · doi:10.1093/bfgp/elr024 · Cited by 245
You, Z., Lei, Y., Gui, J., Huang, D.-S., & Zhou, X. (2010) · Bioinformatics · doi:10.1093/bioinformatics/btq510 · Cited by 227
A strategy for the identification of proteins targeted by thioredoxin
Yano, H., Wong, J. H. H., Lee, Y. M., Cho, M., & Buchanan, B. B. (2001) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.071041998 · Cited by 223
A Pan-plant Protein Complex Map Reveals Deep Conservation and Novel Assemblies
McWhite, C. D., Papoulas, O., Drew, K., Cox, R. M., June, V. M., Dong, O. X., Kwon, T., Wan, C., Salmi, M. L., Roux, S. J., et al. (2020) · Cell · doi:10.1016/j.cell.2020.02.049 · Cited by 218
“Guilt by Association” Is the Exception Rather Than the Rule in Gene Networks
Gillis, J., & Pavlidis, P. (2012) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1002444 · Cited by 214
Modularity and Extreme Edges of the Internet
Eriksen, K. A., Simonsen, I., Maslov, S., & Sneppen, K. (2003) · Physical Review Letters · doi:10.1103/physrevlett.90.148701 · Cited by 213
The use of mass spectrometry for the proteomic analysis of glycosylation
Morelle, W., Canis, K., Chirat, F., Faid, V., & Michalski, J. (2006) · PROTEOMICS · doi:10.1002/pmic.200600129 · Cited by 207
Promises and Challenges of Big Data Computing in Health Sciences
Huang, T., Lan, L., Fang, X., An, P., Min, J., & Wang, F. (2015) · Big Data Research · doi:10.1016/j.bdr.2015.02.002 · Cited by 211
Morris, J. H., Knudsen, G. M., Verschueren, E., Johnson, J. R., Cimermančič, P., Greninger, A. L., & Pico, A. R. (2014) · Nature Protocols · doi:10.1038/nprot.2014.164 · Cited by 210
Advances in membrane receptor screening and analysis
Cooper, M. A. (2004) · Journal of Molecular Recognition · doi:10.1002/jmr.675 · Cited by 204
GCNG: graph convolutional networks for inferring gene interaction from spatial transcriptomics data
Yuan, Y., & Bar-Joseph, Z. (2020) · Genome Biology · doi:10.1186/s13059-020-02214-w · Cited by 194
Analysis of recombinant yeast decapping enzyme
Steiger, M. A., Carr‐Schmid, A., SCHWARTZ, D. C., Kiledjian, M., & Parker, R. (2003) · RNA · doi:10.1261/rna.2151403 · Cited by 188
From Gene Networks to Gene FunctionPreprint
Schlitt, T. (2003) · Genome Research · doi:10.1101/gr.1111403 · Cited by 184
Szymański, J., Bocobza, S. E., Panda, S., Sonawane, P. D., Cárdenas, P. D., Lashbrooke, J., Kamble, A. C., Shahaf, N., Meir, S., Bovy, A. G., et al. (2020) · Nature Genetics · doi:10.1038/s41588-020-0690-6 · Cited by 182
The Impact of Multifunctional Genes on "Guilt by Association" Analysis
Gillis, J., & Pavlidis, P. (2011) · PLoS ONE · doi:10.1371/journal.pone.0017258 · Cited by 179
A high resolution atlas of gene expression in the domestic sheep (Ovis aries)
Clark, E. L., Bush, S. J., McCulloch, M. E. B., Farquhar, I., Young, R. A., Lefèvre, L., Pridans, C., Tsang, H., Wu, C., Afrasiabi, C., et al. (2017) · PLoS Genetics · doi:10.1371/journal.pgen.1006997 · Cited by 176
Molecular Classification and Survival Prediction in Human Gliomas Based on Proteome Analysis
Iwadate, Y., Sakaida, T., Hiwasa, T., Nagai, Y., Ishikura, H., Takiguchi, M., & Yamaura, A. (2004) · Cancer Research · doi:10.1158/0008-5472.can-03-1254 · Cited by 164
HAPPI: an online database of comprehensive human annotated and predicted protein interactions
Chen, J. Y., Mamidipalli, S., & Huan, T. (2009) · BMC Genomics · doi:10.1186/1471-2164-10-s1-s16 · Cited by 164
An Integrated Probabilistic Model for Functional Prediction of Proteins
Deng, M., Chen, T., & Sun, F. (2004) · Journal of Computational Biology · doi:10.1089/1066527041410346 · Cited by 163
Ruiz‐Sola, M. Á., Coman, D., Beck, G., Barja, M. V., Colinas, M., Graf, A., Welsch, R., Rütimann, P., Bühlmann, P., Bigler, L., et al. (2015) · New Phytologist · doi:10.1111/nph.13580 · Cited by 158
Gene networks and the neuroendocrine regulation of puberty
Ojeda, S. R., Dubay, C., Lomniczi, A., Kaidar, G., Matagne, V., Sandau, U. S., & Dissen, G. A. (2009) · Molecular and Cellular Endocrinology · doi:10.1016/j.mce.2009.12.003 · Cited by 162
Emerging tools for real‐time label‐free detection of interactions on functional protein microarrays
Ramachandran, N., Larson, D. N., Stark, P. R. H., Hainsworth, E., & LaBaer, J. (2005) · FEBS Journal · doi:10.1111/j.1742-4658.2005.04971.x · Cited by 155
High-Quality Binary Interactome Mapping
Dreze, M., Monachello, D., Lurin, C., Cusick, M. E., HILL, D. E., Vidal, M., & Falter‐Braun, P. (2010) · Methods in enzymology on CD-ROM/Methods in enzymology · doi:10.1016/s0076-6879(10)70012-4 · Cited by 156
Griffin, J. L., Williams, H. J., Sang, E., Clarke, K., Rae, C. D., & Nicholson, J. K. (2001) · Analytical Biochemistry · doi:10.1006/abio.2001.5096 · Cited by 152
Proteome-Scale Human Interactomics
Luck, K., Sheynkman, G., Zhang, I., & Vidal, M. (2017) · Trends in Biochemical Sciences · doi:10.1016/j.tibs.2017.02.006 · Cited by 142
INstruct: a database of high-quality 3D structurally resolved protein interactome networks
Meyer, M. J., Das, J., Wang, X., & Yu, H. (2013) · Bioinformatics · doi:10.1093/bioinformatics/btt181 · Cited by 144
Interaction generality, a measurement to assess the reliability of a protein-protein interaction
Saito, R. (2002) · Nucleic Acids Research · doi:10.1093/nar/30.5.1163 · Cited by 143
DeepGraphGO: graph neural network for large-scale, multispecies protein function prediction
You, R., Yao, S., Mamitsuka, H., & Zhu, S. (2021) · Bioinformatics · doi:10.1093/bioinformatics/btab270 · Cited by 146
NetGO: improving large-scale protein function prediction with massive network information
You, R., Yao, S., Xiong, Y., Huang, X., Sun, F., Mamitsuka, H., & Zhu, S. (2019) · Nucleic Acids Research · doi:10.1093/nar/gkz388 · Cited by 142
Wu, J., Zhang, N., Hayes, A., Panoutsopoulou, K., & Oliver, S. G. (2004) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0308321100 · Cited by 139
Self-citationHoltorf, H., Guitton, M.-C., & Ralf Reski, A. (2002) · Die Naturwissenschaften · doi:10.1007/s00114-002-0321-3 · Cited by 133
Cannistraci, C. V., Alanis‐Lobato, G., & Ravasi, T. (2013) · Bioinformatics · doi:10.1093/bioinformatics/btt208 · Cited by 126
The metabolome 18 years on: a concept comes of age
Kell, D. B., & Oliver, S. G. (2016) · Metabolomics · doi:10.1007/s11306-016-1108-4 · Cited by 138
Self-citationBang, D., Lim, S., Lee, S., & Kim, S. (2023) · Nature Communications · doi:10.1038/s41467-023-39301-y · Cited by 132
Kim, W., Park, J., & Suh, J. K. (2002) · PubMed · Cited by 125
Refined phylogenetic profiles method for predicting protein-protein interactions
Sun, J., Xu, J., Liu, Z., Liu, Q., Zhao, A., Shi, T., & Li, Y. (2005) · Computer applications in the biosciences · doi:10.1093/bioinformatics/bti532 · Cited by 124
Kaderbhai, N., Broadhurst, D., Ellis, D. I., Goodacre, R., & Kell, D. B. (2003) · Comparative and Functional Genomics · doi:10.1002/cfg.302 · Cited by 120
Saito, R., Suzuki, H., & Hayashizaki, Y. (2003) · Bioinformatics · doi:10.1093/bioinformatics/btg070 · Cited by 117
An Atlas of Protein-Protein Interactions Across Mouse Tissues
Skinnider, M. A., Scott, N. E., Prudova, A., Kerr, C. H., Stoynov, N., Stacey, R. G., Chan, Q. W. T., Rattray, D., Gsponer, J. A., & Foster, L. J. (2021) · Cell · doi:10.1016/j.cell.2021.06.003 · Cited by 108
Advances in Proteomic Technologies
Yarmush, M. L., & Jayaraman, A. (2002) · Annual Review of Biomedical Engineering · doi:10.1146/annurev.bioeng.4.020702.153443 · Cited by 112
Proteome analysis of bronchoalveolar lavage in lung diseases
Magi, B., Bargagli, E., Bini, L., & Rottoli, P. (2006) · PROTEOMICS · doi:10.1002/pmic.200600303 · Cited by 110
Topology of molecular interaction networks
Winterbach, W., Mieghem, P. V., Reinders, M. J. T., Wang, H., & de Ridder, D. (2013) · BMC Systems Biology · doi:10.1186/1752-0509-7-90 · Cited by 109
Protein–Protein Interaction Panel Using Mouse Full-Length cDNAsPreprint
Suzuki, H., Fukunishi, Y., Kagawa, I., Saito, R., Oda, H., Endo, T., Kondo, S., Bono, H. U., Okazaki, Y., & Hayashizaki, Y. (2001) · Genome Research · doi:10.1101/gr.180101 · Cited by 109
Johnson, K. A., & Krishnan, A. (2022) · Genome biology · doi:10.1186/s13059-021-02568-9 · Cited by 111
ANAC017 Coordinates Organellar Functions and Stress Responses by Reprogramming Retrograde Signaling
Meng, X., Li, L., Clercq, I. D., Narsai, R., Xu, Y., Hartmann, A., Lozano-Claros, D., Custovic, E., Lewsey, M. G., Whelan, J., et al. (2019) · PLANT PHYSIOLOGY · doi:10.1104/pp.18.01603 · Cited by 106
Yang, J., Tian, S., Zhao, J., & Zhang, W. (2020) · Pharmacological Research · doi:10.1016/j.phrs.2020.105034 · Cited by 106
GNE: a deep learning framework for gene network inference by aggregating biological information
Kishan, K. C., Li, R., Cui, F., Yu, Q., & Haake, A. R. (2019) · BMC Systems Biology · doi:10.1186/s12918-019-0694-y · Cited by 102
Barja, M. V., Ezquerro, M., Beretta, S., Diretto, G., Florez‐Sarasa, I., Feixes-Prats, E., Fiore, A., Karlova, R., Fernie, A. R., Beekwilder, J., et al. (2021) · New Phytologist · doi:10.1111/nph.17283 · Cited by 103
Biological Mechanisms of Glioma Invasion and Potential Therapeutic Targets
Tysnes, B. B., & Mahesparan, R. (2001) · Journal of Neuro-Oncology · doi:10.1023/a:1012249216117 · Cited by 103
Tovchigrechko, A., Wells, C. A., & Vakser, I. A. (2002) · Protein Science · doi:10.1110/ps.4730102 · Cited by 103
Cornell, M. J., Alam, I. S., Soanes, D. M., Wong, H. M., Hedeler, C., Paton, N. W., Rattray, M., Hubbard, S. J., Talbot, N. J., & Oliver, S. G. (2007) · Genome Research · doi:10.1101/gr.6531807 · Cited by 100
Self-citationFunctional proteomics; current achievements
Yanagida, M. (2002) · Journal of Chromatography B · doi:10.1016/s1570-0232(02)00074-0 · Cited by 99
Explanatory analysis of spectroscopic data using machine learning of simple, interpretable rules
Goodacre, R. (2003) · Vibrational Spectroscopy · doi:10.1016/s0924-2031(03)00045-6 · Cited by 98
Yuan, Q., Xie, J., Xie, J., Zhao, H., & Yang, Y. (2023) · Briefings in Bioinformatics · doi:10.1093/bib/bbad117 · Cited by 93
Genome-wide expression profiling of schizophrenia using a large combined cohort
Mistry, M., Gillis, J. A., & Pavlidis, P. (2012) · Molecular Psychiatry · doi:10.1038/mp.2011.172 · Cited by 92
The Emerging Potential for Network Analysis to Inform Precision Cancer Medicine
Öztürk, K., Dow, M. T., Carlin, D. E., Bejar, R. L., & Carter, H. K. (2018) · Journal of Molecular Biology · doi:10.1016/j.jmb.2018.06.016 · Cited by 90
t-LSE: A Novel Robust Geometric Approach for Modeling Protein-Protein Interaction Networks
Zhu, L., You, Z., Huang, D.-S., & Wang, B. (2013) · PLoS ONE · doi:10.1371/journal.pone.0058368 · Cited by 90
Predicting tissue-specific gene expression from whole blood transcriptome
Basu, M., Wang, K., Ruppin, E., & Hannenhalli, S. S. (2021) · Science Advances · doi:10.1126/sciadv.abd6991 · Cited by 93
The integrated landscape of causal genes and pathways in schizophrenia
Ma, C., Gu, C., Huo, Y., Li, X., & Luo, X. (2018) · Translational Psychiatry · doi:10.1038/s41398-018-0114-x · Cited by 87
SDN2GO: An Integrated Deep Learning Model for Protein Function Prediction
Cai, Y., Wang, J., & Deng, L. (2020) · Frontiers in Bioengineering and Biotechnology · doi:10.3389/fbioe.2020.00391 · Cited by 85
Analysis of Aspergillus nidulans metabolism at the genome-scale
David, H., Özçelik, İ. Ş., Hofmann, G., & Nielsen, J. (2008) · BMC Genomics · doi:10.1186/1471-2164-9-163 · Cited by 86
Roth, C. L., Mastronardi, C. A., Lomniczi, A., Wright, H., Cabrera, R., Mungenast, A. E., Heger, S., Jung, H., Dubay, C., & Ojeda, S. R. (2007) · Endocrinology · doi:10.1210/en.2007-0634 · Cited by 83
Luo, X., You, Z., Zhou, M., Li, S., LEUNG, H. K. N., Xia, Y., & Zhu, Q. (2015) · Scientific Reports · doi:10.1038/srep07702 · Cited by 82
Diet, Nutrition, and Cancer Prevention: The Postgenomic Era
Go, V. L. W., Butrum, R. R., & Wong, D. A. (2003) · Journal of Nutrition · doi:10.1093/jn/133.11.3830s · Cited by 82
Efficient embedding of complex networks to hyperbolic space via their Laplacian
Alanis‐Lobato, G., Mier, P., & Andrade-Navarro, M. A. (2016) · Scientific Reports · doi:10.1038/srep30108 · Cited by 82
Li, J., Liu, C., Chen, Y., Gao, C., Wang, M., Ma, X., Zhang, W., Zhuang, J., Yao, Y., & Sun, C. (2019) · Frontiers in Genetics · doi:10.3389/fgene.2019.01119 · Cited by 77
Cesa‐Bianchi, N., Ré, M., & Valentini, G. (2011) · Machine Learning · doi:10.1007/s10994-011-5271-6 · Cited by 77
KELLER: estimating time-varying interactions between genes
Song, L., Kolar, M., & Xing, E. P. (2009) · Bioinformatics · doi:10.1093/bioinformatics/btp192 · Cited by 80
Increasing confidence of protein interactomes using network topological metrics
Chen, J., Hsu, W., Lee, M. L., & Ng, S.-K. (2006) · Bioinformatics · doi:10.1093/bioinformatics/btl335 · Cited by 80
Advances in protein-protein interaction network analysis for Parkinson's disease
Tomkins, J. E., & Manzoni, C. (2021) · Neurobiology of Disease · doi:10.1016/j.nbd.2021.105395 · Cited by 78
The role of indirect connections in gene networks in predicting function
Gillis, J., & Pavlidis, P. (2011) · Bioinformatics · doi:10.1093/bioinformatics/btr288 · Cited by 74
Genotype–phenotype mapping: genes as computer programs
Kell, D. B. (2002) · Trends in Genetics · doi:10.1016/s0168-9525(02)02765-8 · Cited by 74
Dürr, M., Escobar‐Henriques, M., Merz, S., Geimer, S., Langer, T., & Westermann, B. (2006) · Molecular Biology of the Cell · doi:10.1091/mbc.e06-01-0053 · Cited by 73
Liesecke, F., Daudu, D., de Bernonville, R. D., Besseau, S., Clastre, M., Courdavault, V., Craene, J. D., Crèche, J., Giglioli‐Guivarc’h, N., Glévarec, G., et al. (2018) · Scientific Reports · doi:10.1038/s41598-018-29077-3 · Cited by 70
Decottignies, A., Evain, A., & Ghislain, M. (2003) · Yeast · doi:10.1002/yea.1071 · Cited by 69
Effect of training datasets on support vector machine prediction of protein‐protein interactions
Lo, S. L., Cai, C., Chen, Y., & Chung, M. C. M. (2005) · PROTEOMICS · doi:10.1002/pmic.200401118 · Cited by 67
A Two-Stage Geometric Method for Pruning Unreliable Links in Protein-Protein Networks
Zhu, L., Deng, S.-P., & Huang, D.-S. (2015) · IEEE Transactions on NanoBioscience · doi:10.1109/tnb.2015.2420754 · Cited by 66
Itzel, T., Scholz, P., Maass, T., Krupp, M., Marquardt, J. U., Strand, S., Becker, D., Staib, F., Binder, H., Roessler, S. K., et al. (2014) · Bioinformatics · doi:10.1093/bioinformatics/btu586 · Cited by 66
Leveraging the Cell Ontology to classify unseen cell types
Wang, S., Pisco, A. O., McGeever, A., Brbić, M., Žitnik, M., Darmanis, S., Leskovec, J., Karkanias, J., & Altman, R. B. (2021) · Nature Communications · doi:10.1038/s41467-021-25725-x · Cited by 87
Pellegrini, L., Passer, B. J., Cañelles, M., Lefterov, I. M., Ganjei, J. K., Fowlkes, B. J., Koonin, E. V., & D'adamio, L. (2001) · Journal of Alzheimer s Disease · doi:10.3233/jad-2001-3203 · Cited by 65
Metadata
- Authors
- Oliver, S.
- Affiliations
- University of Manchester (GB)
- Corresponding author
- Oliver, Stephen
- ORCID
- Oliver, Stephen
- Venue
- Nature
- Published
- 2000-02
- Volume
- 403
- Issue
- 6770
- Pages
- 601-602
- ISSN
- 0028-0836 (ISSN-L)
- 1476-4687
- OpenAlex
- W2770983033
- Cited by
- 557
- References
- 17
- Citations by year
- 2026: 13 · 2025: 15 · 2024: 20 · 2023: 21 · 2022: 36 · 2021: 40 · 2020: 26 · 2019: 27 · 2018: 37 · 2017: 40 · 2016: 16 · 2015: 31 · 2014: 25 · 2013: 23 · 2012: 19
- FWCI
- 8.08
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Nature (publishedVersion)
- PubMed (publishedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- Research Explorer (The University of Manchester) (submittedVersion)
- 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
- protein-protein interaction, protein function prediction, guilt by association, yeast proteome, protein-protein interaction network
- MeSH terms
- Fungal Proteins, Protein Binding, Proteins, Saccharomyces cerevisiae, Genome, Fungal, Two-Hybrid System Techniques
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