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For: Azevedo H, Moreira-Filho CA. Topological robustness analysis of protein interaction networks reveals key targets for overcoming chemotherapy resistance in glioma. Sci Rep 2015;5:16830. [PMID: 26582089 DOI: 10.1038/srep16830] [Cited by in Crossref: 27] [Cited by in F6Publishing: 21] [Article Influence: 3.9] [Reference Citation Analysis]
Number Citing Articles
1 Schwill M, Tamaskovic R, Gajadhar AS, Kast F, White FM, Plückthun A. Systemic analysis of tyrosine kinase signaling reveals a common adaptive response program in a HER2-positive breast cancer. Sci Signal 2019;12:eaau2875. [PMID: 30670633 DOI: 10.1126/scisignal.aau2875] [Cited by in Crossref: 16] [Cited by in F6Publishing: 9] [Article Influence: 5.3] [Reference Citation Analysis]
2 Conforte AJ, Tuszynski JA, da Silva FAB, Carels N. Signaling Complexity Measured by Shannon Entropy and Its Application in Personalized Medicine. Front Genet 2019;10:930. [PMID: 31695721 DOI: 10.3389/fgene.2019.00930] [Cited by in Crossref: 6] [Cited by in F6Publishing: 5] [Article Influence: 2.0] [Reference Citation Analysis]
3 Alur VC, Raju V, Vastrad B, Vastrad C. Mining Featured Biomarkers Linked with Epithelial Ovarian CancerBased on Bioinformatics. Diagnostics (Basel) 2019;9:E39. [PMID: 30970615 DOI: 10.3390/diagnostics9020039] [Reference Citation Analysis]
4 Eicher T, Kinnebrew G, Patt A, Spencer K, Ying K, Ma Q, Machiraju R, Mathé AEA. Metabolomics and Multi-Omics Integration: A Survey of Computational Methods and Resources. Metabolites 2020;10:E202. [PMID: 32429287 DOI: 10.3390/metabo10050202] [Cited by in Crossref: 19] [Cited by in F6Publishing: 15] [Article Influence: 9.5] [Reference Citation Analysis]
5 Uddin R, Jamil F. Prioritization of potential drug targets against P. aeruginosa by core proteomic analysis using computational subtractive genomics and Protein-Protein interaction network. Computational Biology and Chemistry 2018;74:115-22. [DOI: 10.1016/j.compbiolchem.2018.02.017] [Cited by in Crossref: 25] [Cited by in F6Publishing: 19] [Article Influence: 6.3] [Reference Citation Analysis]
6 Recamonde-mendoza M, Werhli AV, Biolo A. Systems biology approach identifies key regulators and the interplay between miRNAs and transcription factors for pathological cardiac hypertrophy. Gene 2019;698:157-69. [DOI: 10.1016/j.gene.2019.02.056] [Cited by in Crossref: 5] [Cited by in F6Publishing: 6] [Article Influence: 1.7] [Reference Citation Analysis]
7 Yue J, Xu W, Ban R, Huang S, Miao M, Tang X, Liu G, Liu Y. PTIR: Predicted Tomato Interactome Resource. Sci Rep 2016;6:25047. [PMID: 27121261 DOI: 10.1038/srep25047] [Cited by in Crossref: 16] [Cited by in F6Publishing: 14] [Article Influence: 2.7] [Reference Citation Analysis]
8 Das AB. Small-world networks of prognostic genes associated with lung adenocarcinoma development. Genomics 2020;112:4078-88. [PMID: 32659327 DOI: 10.1016/j.ygeno.2020.07.018] [Cited by in Crossref: 1] [Article Influence: 0.5] [Reference Citation Analysis]
9 M B, P C. Comparative analysis of differential proteome-wide protein-protein interaction network of Methanobrevibacter ruminantium M1. Biochem Biophys Rep 2019;20:100698. [PMID: 31763465 DOI: 10.1016/j.bbrep.2019.100698] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 0.3] [Reference Citation Analysis]
10 Hu JX, Thomas CE, Brunak S. Network biology concepts in complex disease comorbidities. Nat Rev Genet 2016;17:615-29. [PMID: 27498692 DOI: 10.1038/nrg.2016.87] [Cited by in Crossref: 143] [Cited by in F6Publishing: 127] [Article Influence: 23.8] [Reference Citation Analysis]
11 Trigos AS, Pearson RB, Papenfuss AT, Goode DL. How the evolution of multicellularity set the stage for cancer. Br J Cancer 2018;118:145-52. [PMID: 29337961 DOI: 10.1038/bjc.2017.398] [Cited by in Crossref: 40] [Cited by in F6Publishing: 35] [Article Influence: 10.0] [Reference Citation Analysis]
12 Rizzetto S, Csikász-Nagy A. Toward Large-Scale Computational Prediction of Protein Complexes. Methods Mol Biol 2018;1819:271-95. [PMID: 30421409 DOI: 10.1007/978-1-4939-8618-7_13] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 0.3] [Reference Citation Analysis]
13 Duran CL, Lee DW, Jung JU, Ravi S, Pogue CB, Toussaint LG, Bayless KJ, Sitcheran R. NIK regulates MT1-MMP activity and promotes glioma cell invasion independently of the canonical NF-κB pathway. Oncogenesis 2016;5:e231. [PMID: 27270613 DOI: 10.1038/oncsis.2016.39] [Cited by in Crossref: 13] [Cited by in F6Publishing: 14] [Article Influence: 2.2] [Reference Citation Analysis]
14 Moreira-Filho CA, Bando SY, Bertonha FB, Ferreira LR, Vinhas CF, Oliveira LHB, Zerbini MCN, Furlanetto G, Chaccur P, Carneiro-Sampaio M. Minipuberty and Sexual Dimorphism in the Infant Human Thymus. Sci Rep 2018;8:13169. [PMID: 30177771 DOI: 10.1038/s41598-018-31583-3] [Cited by in Crossref: 10] [Cited by in F6Publishing: 8] [Article Influence: 2.5] [Reference Citation Analysis]
15 Cataldo R, Leuzzi M, Alfinito E. Modelling and Development of Electrical Aptasensors: A Short Review. Chemosensors 2018;6:20. [DOI: 10.3390/chemosensors6020020] [Cited by in Crossref: 5] [Cited by in F6Publishing: 4] [Article Influence: 1.3] [Reference Citation Analysis]
16 Chen YR, Huang HC, Lin CC. Regulatory feedback loops bridge the human gene regulatory network and regulate carcinogenesis. Brief Bioinform 2019;20:976-84. [PMID: 29194477 DOI: 10.1093/bib/bbx166] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 0.3] [Reference Citation Analysis]
17 Malhotra AG, Jha M, Singh S, Pandey KM. Construction of a Comprehensive Protein-Protein Interaction Map for Vitiligo Disease to Identify Key Regulatory Elements: A Systemic Approach. Interdiscip Sci 2018;10:500-14. [PMID: 28290051 DOI: 10.1007/s12539-017-0213-z] [Cited by in Crossref: 5] [Cited by in F6Publishing: 5] [Article Influence: 1.0] [Reference Citation Analysis]
18 Conforte AJ, Alves L, Coelho FC, Carels N, da Silva FAB. Modeling Basins of Attraction for Breast Cancer Using Hopfield Networks. Front Genet 2020;11:314. [PMID: 32318098 DOI: 10.3389/fgene.2020.00314] [Cited by in Crossref: 5] [Cited by in F6Publishing: 3] [Article Influence: 2.5] [Reference Citation Analysis]
19 Hsu MK, Pan CL, Chen FC. Functional divergence and convergence between the transcript network and gene network in lung adenocarcinoma. Onco Targets Ther 2016;9:335-47. [PMID: 26834492 DOI: 10.2147/OTT.S94897] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 0.2] [Reference Citation Analysis]
20 Prathiviraj R, Berchmans S, Chellapandi P. Analysis of modularity in proteome-wide protein interaction networks of Methanothermobacter thermautotrophicus strain ΔH and metal-loving bacteria. J Proteins Proteom 2019;10:179-90. [DOI: 10.1007/s42485-019-00019-5] [Cited by in Crossref: 7] [Cited by in F6Publishing: 3] [Article Influence: 2.3] [Reference Citation Analysis]
21 Torres-Ávila JF, Espitia-Pérez L, Bonatto D, Silva FRD, Oliveira IM, Silva LFO, Corrêa DS, Dias JF, Silva JD, Henriques JAP. Systems chemo-biology analysis of DNA damage response and cell cycle effects induced by coal exposure. Genet Mol Biol 2020;43:e20190134. [PMID: 32609278 DOI: 10.1590/1678-4685-GMB-2019-0134] [Cited by in Crossref: 2] [Cited by in F6Publishing: 3] [Article Influence: 1.0] [Reference Citation Analysis]
22 Jiang W, Zhang Z, Sun Y, Zhang Y, Zhang L, Liu H, Peng R. Construction and analysis of a diabetic nephropathy related protein-protein interaction network reveals nine critical and functionally associated genes. Comput Biol Chem 2019;83:107115. [PMID: 31561072 DOI: 10.1016/j.compbiolchem.2019.107115] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 0.3] [Reference Citation Analysis]