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For: Bernardo-Faura M, Massen S, Falk CS, Brady NR, Eils R. Data-derived modeling characterizes plasticity of MAPK signaling in melanoma. PLoS Comput Biol 2014;10:e1003795. [PMID: 25188314 DOI: 10.1371/journal.pcbi.1003795] [Cited by in Crossref: 18] [Cited by in F6Publishing: 15] [Article Influence: 2.6] [Reference Citation Analysis]
Number Citing Articles
1 Wang Z, Deisboeck TS. Dynamic Targeting in Cancer Treatment. Front Physiol 2019;10:96. [PMID: 30890944 DOI: 10.3389/fphys.2019.00096] [Cited by in Crossref: 12] [Cited by in F6Publishing: 10] [Article Influence: 6.0] [Reference Citation Analysis]
2 Albrecht M, Lucarelli P, Kulms D, Sauter T. Computational models of melanoma. Theor Biol Med Model 2020;17:8. [PMID: 32410672 DOI: 10.1186/s12976-020-00126-7] [Cited by in Crossref: 2] [Cited by in F6Publishing: 1] [Article Influence: 2.0] [Reference Citation Analysis]
3 Bernardo-Faura M, Rinas M, Wirbel J, Pertsovskaya I, Pliaka V, Messinis DE, Vila G, Sakellaropoulos T, Faigle W, Stridh P, Behrens JR, Olsson T, Martin R, Paul F, Alexopoulos LG, Villoslada P, Saez-Rodriguez J. Prediction of combination therapies based on topological modeling of the immune signaling network in multiple sclerosis. Genome Med 2021;13:117. [PMID: 34271980 DOI: 10.1186/s13073-021-00925-8] [Reference Citation Analysis]
4 Roller DG, Capaldo B, Bekiranov S, Mackey AJ, Conaway MR, Petricoin EF, Gioeli D, Weber MJ. Combinatorial drug screening and molecular profiling reveal diverse mechanisms of intrinsic and adaptive resistance to BRAF inhibition in V600E BRAF mutant melanomas. Oncotarget 2016;7:2734-53. [PMID: 26673621 DOI: 10.18632/oncotarget.6548] [Cited by in Crossref: 13] [Cited by in F6Publishing: 12] [Article Influence: 2.6] [Reference Citation Analysis]
5 Cordaro FG, De Presbiteris AL, Camerlingo R, Mozzillo N, Pirozzi G, Cavalcanti E, Manca A, Palmieri G, Cossu A, Ciliberto G, Ascierto PA, Travali S, Patriarca EJ, Caputo E. Phenotype characterization of human melanoma cells resistant to dabrafenib. Oncol Rep 2017;38:2741-51. [PMID: 29048639 DOI: 10.3892/or.2017.5963] [Cited by in Crossref: 15] [Cited by in F6Publishing: 15] [Article Influence: 3.8] [Reference Citation Analysis]
6 Gao G, Yao Z, Shen J, Liu Y. Identification of Key miRNAs in the Treatment of Dabrafenib-Resistant Melanoma. Biomed Res Int 2021;2021:5524486. [PMID: 33880366 DOI: 10.1155/2021/5524486] [Reference Citation Analysis]
7 Penas DR, Henriques D, González P, Doallo R, Saez-Rodriguez J, Banga JR. A parallel metaheuristic for large mixed-integer dynamic optimization problems, with applications in computational biology. PLoS One 2017;12:e0182186. [PMID: 28813442 DOI: 10.1371/journal.pone.0182186] [Cited by in Crossref: 7] [Cited by in F6Publishing: 3] [Article Influence: 1.8] [Reference Citation Analysis]
8 Henriques D, Rocha M, Saez-Rodriguez J, Banga JR. Reverse engineering of logic-based differential equation models using a mixed-integer dynamic optimization approach. Bioinformatics 2015;31:2999-3007. [PMID: 26002881 DOI: 10.1093/bioinformatics/btv314] [Cited by in Crossref: 16] [Cited by in F6Publishing: 11] [Article Influence: 2.7] [Reference Citation Analysis]
9 Keller R, Klein M, Thomas M, Dräger A, Metzger U, Templin MF, Joos TO, Thasler WE, Zell A, Zanger UM. Coordinating Role of RXRα in Downregulating Hepatic Detoxification during Inflammation Revealed by Fuzzy-Logic Modeling. PLoS Comput Biol 2016;12:e1004431. [PMID: 26727233 DOI: 10.1371/journal.pcbi.1004431] [Cited by in Crossref: 17] [Cited by in F6Publishing: 16] [Article Influence: 3.4] [Reference Citation Analysis]
10 Zhang X, Bai L, Guo N, Cai B. Transcriptomic analyses revealed the effect of Funneliformis mosseae on genes expression in Fusarium oxysporum. PLoS One 2020;15:e0234448. [PMID: 32735565 DOI: 10.1371/journal.pone.0234448] [Reference Citation Analysis]
11 Dorel M, Barillot E, Zinovyev A, Kuperstein I. Network-based approaches for drug response prediction and targeted therapy development in cancer. Biochem Biophys Res Commun 2015;464:386-91. [PMID: 26086105 DOI: 10.1016/j.bbrc.2015.06.094] [Cited by in Crossref: 26] [Cited by in F6Publishing: 18] [Article Influence: 4.3] [Reference Citation Analysis]
12 Pennisi M, Russo G, Di Salvatore V, Candido S, Libra M, Pappalardo F. Computational modeling in melanoma for novel drug discovery. Expert Opin Drug Discov 2016;11:609-21. [PMID: 27046143 DOI: 10.1080/17460441.2016.1174688] [Cited by in Crossref: 12] [Cited by in F6Publishing: 12] [Article Influence: 2.4] [Reference Citation Analysis]
13 Karakuş O, Kuruoğlu EE, Altınkaya MA. One‐day ahead wind speed/power prediction based on polynomial autoregressive model. IET Renewable Power Generation 2017;11:1430-9. [DOI: 10.1049/iet-rpg.2016.0972] [Cited by in Crossref: 54] [Cited by in F6Publishing: 4] [Article Influence: 13.5] [Reference Citation Analysis]
14 Nyman E, Stein RR, Jing X, Wang W, Marks B, Zervantonakis IK, Korkut A, Gauthier NP, Sander C. Perturbation biology links temporal protein changes to drug responses in a melanoma cell line. PLoS Comput Biol 2020;16:e1007909. [PMID: 32667922 DOI: 10.1371/journal.pcbi.1007909] [Cited by in Crossref: 3] [Cited by in F6Publishing: 2] [Article Influence: 3.0] [Reference Citation Analysis]
15 Akhmetzhanov AR, Kim JW, Sullivan R, Beckman RA, Tamayo P, Yeang C. Modelling bistable tumour population dynamics to design effective treatment strategies. Journal of Theoretical Biology 2019;474:88-102. [DOI: 10.1016/j.jtbi.2019.05.005] [Cited by in Crossref: 5] [Cited by in F6Publishing: 4] [Article Influence: 2.5] [Reference Citation Analysis]