Fields S, Song O-K. A novel genetic system to detect protein–protein interactions. Nature. 1989;340(6230):245–6.
Glass JI, Hutchison CA III, Smith HO, Venter JC. A systems biology tour de force for a near-minimal bacterium. Mol Syst Biol. 2009;5(1):330.
Winzeler EA, Shoemaker DD, Astromoff A, Liang H, Anderson K, Andre B, et al. Functional characterization of the S cerevisiae genome by gene deletion and parallel analysis. Science. 1999;285(5429):901–6.
Zhang R, Lin Y. DEG 5.0, a database of essential genes in both prokaryotes and eukaryotes. Nucleic Acids Res. 2009;37(suppl_1):D455–8.
Clatworthy AE, Pierson E, Hung DT. Targeting virulence: a new paradigm for antimicrobial therapy. Nat Chem Biol. 2007;3(9):541–8.
Giaever G, Chu AM, Ni L, Connelly C, Riles L, Veronneau S, et al. Functional profiling of the Saccharomyces cerevisiae genome. Nature. 2002;418(6896):387–91. https://doi.org/10.1038/nature00935.
Roemer T, Jiang B, Davison J, Ketela T, Veillette K, Breton A, et al. Large-scale essential gene identification in Candida albicans and applications to antifungal drug discovery. Mol Microbiol. 2003;50(1):167–81.
Cullen LM, Arndt GM. Genome-wide screening for gene function using RNAi in mammalian cells. Immunol Cell Biol. 2005;83(3):217–23.
Hahn MW, Kern AD. Comparative genomics of centrality and essentiality in three eukaryotic protein-interaction networks. Mol Biol Evol. 2005;22(4):803–6. https://doi.org/10.1093/molbev/msi072.
Joy MP, Brock A, Ingber DE, Huang S. High-betweenness proteins in the yeast protein interaction network. J Biomed Biotechnol. 2005;2005(2):96–103. https://doi.org/10.1155/JBB.2005.96.
Wuchty S, Stadler PF. Centers of complex networks. J Theor Biol. 2003;223(1):45–53. https://doi.org/10.1016/s0022-5193(03)00071-7.
Article MathSciNet MATH Google Scholar
Estrada E, Rodriguez-Velazquez JA. Subgraph centrality in complex networks. Phys Rev E. 2005;71(5 Pt 2): 056103. https://doi.org/10.1103/PhysRevE.71.056103.
Article MathSciNet Google Scholar
Bonacich P. Power and centrality: a family of measures. Am J Sociol. 1987;92:12.
Stephenson K, Zelen M. Rethinking centrality: methods and examples. Soc Netw. 1989;11(1):1–37.
Article MathSciNet Google Scholar
Wang J, Li M, Wang H, Pan Y. Bioinformatics. Identification of essential proteins based on edge clustering coefficient. IEEE/ACM Trans Comput Biol. 2011;9(4):1070–80.
Acencio ML, Lemke N. Towards the prediction of essential genes by integration of network topology, cellular localization and biological process information. BMC Bioinform. 2009;10(1):290. https://doi.org/10.1186/1471-2105-10-290.
Fraser HB, Hirsh AE, Steinmetz LM, Scharfe C, Feldman MW. Evolutionary rate in the protein interaction network. Science. 2002;296(5568):750–2. https://doi.org/10.1126/science.1068696.
Jordan IK, Rogozin IB, Wolf YI, Koonin EV. Essential genes are more evolutionarily conserved than are nonessential genes in bacteria. Genome Res. 2002;12(6):962–8.
Batada NN, Hurst LD, Tyers M. Evolutionary and physiological importance of hub proteins. PLoS Comput Biol. 2006;2(7): e88. https://doi.org/10.1371/journal.pcbi.0020088.
Sharp PM. Determinants of DNA sequence divergence between Escherichia coli and Salmonella typhimurium: codon usage, map position, and concerted evolution. J Mol Evol. 1991;33:23–33.
Rocha EP, Danchin A. An analysis of determinants of amino acids substitution rates in bacterial proteins. Mol Biol Evol. 2004;21(1):108–16. https://doi.org/10.1093/molbev/msh004.
Wang J, Peng X, Li M, Pan Y. Construction and application of dynamic protein interaction network based on time course gene expression data. Proteomics. 2013;13(2):301–12. https://doi.org/10.1002/pmic.201200277.
Xiao Q, Wang J, Peng X, Wu F-X, Pan Y. Identifying essential proteins from active PPI networks constructed with dynamic gene expression. BMC Genomics. 2015;16:1–7.
Zhang Y, Lin H, Yang Z, Wang J. Construction of dynamic probabilistic protein interaction networks for protein complex identification. BMC Bioinform. 2016;17:1–13.
Li M, Meng X, Zheng R, Wu FX, Li Y, Pan Y, et al. Identification of protein complexes by using a spatial and temporal active protein interaction network. IEEE/ACM Trans Comput Biol Bioinform. 2017;17:817–27.
Tang X, Wang J, Zhong J, Pan Y. Predicting essential proteins based on weighted degree centrality. IEEE/ACM Trans Comput Biol Bioinform. 2013;11(2):407–18.
Zhang X, Xiao W, Hu X. Predicting essential proteins by integrating orthology, gene expressions, and PPI networks. PLoS ONE. 2018;13(4): e0195410.
Li G, Li M, Wang J, Wu J, Wu F-X, Pan Y. Predicting essential proteins based on subcellular localization, orthology and PPI networks. BMC Bioinform. 2016;17(8):571–81.
Li M, Zhang H, Wang JX, Pan Y. A new essential protein discovery method based on the integration of protein-protein interaction and gene expression data. BMC Syst Biol. 2012;6:15. https://doi.org/10.1186/1752-0509-6-15.
Zhong J, Tang C, Peng W, Xie M, Sun Y, Tang Q, et al. A novel essential protein identification method based on PPI networks and gene expression data. BMC Bioinform. 2021;22(1):248. https://doi.org/10.1186/s12859-021-04175-8.
Zhang W, Xu J, Zou X. Predicting essential proteins by integrating network topology, subcellular localization information, gene expression profile and go annotation data. IEEE/ACM Trans Comput Biol Bioinform. 2019;17(6):2053–61.
Peng W, Wang J, Wang W, Liu Q, Wu FX, Pan Y. Iteration method for predicting essential proteins based on orthology and protein-protein interaction networks. BMC Syst Biol. 2012;6(1):87. https://doi.org/10.1186/1752-0509-6-87.
Zhang Z, Jiang M, Wu D, Zhang W, Yan W, Qu X. A novel method for identifying essential proteins based on non-negative matrix tri-factorization. Front Genet. 2021;12: 709660.
Li G, Li M, Wang J, Li Y, Pan Y. United neighborhood closeness centrality and orthology for predicting essential proteins. IEEE/ACM Trans Comput Biol Bioinform. 2020;17(4):1451–8. https://doi.org/10.1109/TCBB.2018.2889978.
Li G, Li M, Peng W, Li Y, Pan Y, Wang J. A novel extended Pareto optimality consensus model for predicting essential proteins. J Theor Biol. 2019;480:141–9.
Xenarios I, Salwinski L, Duan XJ, Higney P, Kim SM, Eisenberg D. DIP, the database of interacting proteins: a research tool for studying cellular networks of protein interactions. Nucleic Acids Res. 2002;30(1):303–5. https://doi.org/10.1093/nar/30.1.303.
Yu H, Luscombe NM, Qian J, Gerstein M. Genomic analysis of gene expression relationships in transcriptional regulatory networks. Trends Genet. 2003;19(8):422–7. https://doi.org/10.1016/S0168-9525(03)00175-6.
Nepusz T, Yu H, Paccanaro A. Detecting overlapping protein complexes in protein-protein interaction networks. Nat Methods. 2012;9(5):471–2. https://doi.org/10.1038/nmeth.1938.
Mewes HW, Amid C, Arnold R, Frishman D, Guldener U, Mannhaupt G, et al. MIPS: analysis and annotation of proteins from whole genomes. Nucleic Acids Res. 2004;32:D41–4. https://doi.org/10.1093/nar/gkh092.
Cherry JM, Adler C, Ball C, Chervitz SA, Dwight SS, Hester ET, et al. SGD: Saccharomyces Genome Database. Nucleic Acids Res. 1998;26(1):73–9. https://doi.org/10.1093/nar/26.1.73.
Saccharomyces Genome Deletion Project. http://www-sequence.stanford.edu/group/.
Tu BP, Kudlicki A, Rowicka M, McKnight SL. Logic of the yeast metabolic cycle: temporal compartmentalization of cellular processes. Science. 2005;310(5751):1152–8. https://doi.org/10.1126/science.1120499.
COMPARTMENTS. http://compartments.jensenlab.org. Accessed 28 Dec 2014.
Östlund G, Schmitt T, Forslund K, Köstler T, Messina DN, Roopra S, et al. InParanoid 7: new algorithms and tools for eukaryotic orthology analysis. Nucleic Acids Res. 2010;38:D196–203.
Zhou Y, Zhou B, Pache L, Chang M, Khodabakhshi AH, Tanaseichuk O, et al. Metascape provides a biologist-oriented resource for the analysis of systems-level datasets. Nat Commun. 2019;10(1):1523. https://doi.org/10.1038/s41467-019-09234-6.
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