The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
Lethality and centrality in protein networks
Open accessAbstract
Proteins are traditionally identified on the basis of their individual actions as catalysts, signalling molecules, or building blocks in cells and microorganisms. But our post-genomic view is expanding the protein's role into an element in a network of protein–protein interactions as well, in which it has a contextual or cellular function within functional modules. Here we provide quantitative support for this idea by demonstrating that the phenotypic consequence of a single gene deletion in the yeast Saccharomyces cerevisiae is affected to a large extent by the topological position of its protein product in the complex hierarchical web of molecular interactions.
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Citations
Cites
Error and attack tolerance of complex networks
Albert, R., Jeong, H., & Barabási, A.-L. (2000) · Nature · doi:10.1038/35019019 · Cited by 7,534
Self-citationA 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
Classes of small-world networks
Amaral, L. A. N., Scala, A., Barthélémy, M., & Stanley, H. E. (2000) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.200327197 · Cited by 3,051
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Life cycles of successful genes
Hoffmann, R., & Valencia, A. (2003) · Trends in Genetics · doi:10.1016/s0168-9525(02)00014-8 · Cited by 69
Hsing, M., Byler, K. G., & Cherkasov, A. (2008) · BMC Systems Biology · doi:10.1186/1752-0509-2-80 · Cited by 66
Comparing Pearson, Spearman and Hoeffding’s D measure for gene expression association analysis
FUJITA, A., SATO, J. R., DEMASI, M. A. A., SOGAYAR, M. C., FERREIRA, C. E., & MIYANO, S. (2009) · Journal of Bioinformatics and Computational Biology · doi:10.1142/s0219720009004230 · Cited by 64
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Waardenberg, A. J., Ramialison, M., Bouveret, R., & Harvey, R. P. (2014) · Cold Spring Harbor Perspectives in Medicine · doi:10.1101/cshperspect.a013839 · Cited by 59
Noh, H. J., Ponting, C. P., Boulding, H. C., Meader, S., Betancur, C., Buxbaum, J. D., Pinto, D., Marshall, C. R., Lionel, A. C., Scherer, S. W., et al. (2013) · PLoS Genetics · doi:10.1371/journal.pgen.1003523 · Cited by 54
Systems biology in neuroscience: bridging genes to cognition
Grant, S. G. (2003) · Current Opinion in Neurobiology · doi:10.1016/j.conb.2003.09.016 · Cited by 53
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Tëmkin, I., & Eldredge, N. (2015) · Interdisciplinary Evolution Research · doi:10.1007/978-3-319-15045-1_6 · Cited by 49
Probiotic alleviate fluoride-induced memory impairment by reconstructing gut microbiota in mice
Xin, J., Wang, H., Sun, N., Bughio, S., Zeng, D., Li, L., Wang, Y., Khalique, A., Zeng, Y., Pan, K., et al. (2021) · Ecotoxicology and Environmental Safety · doi:10.1016/j.ecoenv.2021.112108 · Cited by 42
Structural and dynamical analysis of biological networks
Klein, C., Marino, A., Sagot, M.-F., Vieira Milreu, P., & Brilli, M. (2012) · Briefings in Functional Genomics · doi:10.1093/bfgp/els030 · Cited by 34
Biological process linkage networks
Dotan-Cohen, D., Letovsky, S., Melkman, A. A., & Kasif, S. (2009) · PLoS ONE · doi:10.1371/journal.pone.0005313 · Cited by 38
Evolving complexity: how tinkering shapes cells, software and ecological networks.
Solé, R., & Valverde, S. (2020) · Philosophical Transactions of the Royal Society B: Biological Sciences · doi:10.1098/rstb.2019.0325 · Cited by 37
Farooqui, A., Tazyeen, S., Ahmed, M. M., Alam, A., Ali, S., Malik, M. Z., Ali, S., & Ishrat, R. (2018) · Scientific Reports · doi:10.1038/s41598-018-28375-0 · Cited by 30
Janin, J., & Wodak, S. J. (2002) · Advances in Protein Chemistry · doi:10.1016/s0065-3233(02)61000-9 · Cited by 31
Mao, Y., Fisher, D. W., Yang, S., Keszycki, R. M., & Dong, H. (2020) · PLOS ONE · doi:10.1371/journal.pone.0226021 · Cited by 28
Ouyang, S., Tang, R., Liu, Z., Ma, F., Li, Y., & Wu, J. (2017) · Molecular Medicine Reports · doi:10.3892/mmr.2017.7118 · Cited by 25
Onisiforou, A., & Spyrou, G. M. (2021) · Briefings in Bioinformatics · doi:10.1093/bib/bbab141 · Cited by 23
“whereas the deletion of a random node with few connections does not influence the topology of the network [65, 66].”
BackgroundMohseni Behbahani, Y., Laine, E., & Carbone, A. (2023) · Bioinformatics · doi:10.1093/bioinformatics/btad231 · Cited by 23
Graph theory and stability analysis of protein complex interaction networks
Huang, C., Chen, T., & Ng, K. (2016) · IET Systems Biology · doi:10.1049/iet-syb.2015.0007 · Cited by 18
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Paparo, G. D., Müller, M., Comellas, F., & Martin-Delgado, M. A. (2014) · The European Physical Journal Plus · doi:10.1140/epjp/i2014-14150-y · Cited by 17
Duan, D., Hanson, M., Holland, D. O., & Johnson, M. E. (2022) · Scientific Reports · doi:10.1038/s41598-022-09259-w · Cited by 15
Early Systems Biology and Prebiotic Networks
Shenhav, B., Solomon, A., Lancet, D., & Kafri, R. (2005) · Lecture Notes in Computer Science · doi:10.1007/978-3-540-32126-2_2 · Cited by 13
Jaemthaworn, T., Kalapanulak, S., & Saithong, T. (2021) · Scientific Reports · doi:10.1038/s41598-021-86806-x · Cited by 7
Extended physics as a theoretical framework for systems biology?
Miquel, P.-A. (2011) · Progress in Biophysics and Molecular Biology · doi:10.1016/j.pbiomolbio.2011.03.006 · Cited by 6
Mournetas, V., Nunes, Q. M., Murray, P. A., Sanderson, C. M., & Fernig, D. G. (2014) · PeerJ · doi:10.7717/peerj.618 · Cited by 2
Hacisuleyman, A., Gul, A., & Erman, B. (2025) · Proteins: Structure, Function, and Bioinformatics · doi:10.1002/prot.26795 · Cited by 1
Metadata
- Authors
- Jeong, H., Mason, S. P., Barabási, A.-L., & Oltvai, Z. N.
- Venue
- Nature
- Published
- 2001-05
- Volume
- 411
- Issue
- 6833
- Pages
- 41-42
- ISSN
- 0028-0836 (ISSN-L)
- 1476-4687
- OpenAlex
- W2130790725
- Cited by
- 5,287
- References
- 3
- FWCI
- 44.73
- Type
- journal article
- Language
- en
- Open access
- green
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