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Cited by in F6Publishing
For: An G. Introduction of a Framework for Dynamic Knowledge Representation of the Control Structure of Transplant Immunology: Employing the Power of Abstraction with a Solid Organ Transplant Agent-Based Model. Front Immunol 2015;6:561. [PMID: 26594211 DOI: 10.3389/fimmu.2015.00561] [Cited by in Crossref: 4] [Cited by in F6Publishing: 3] [Article Influence: 0.6] [Reference Citation Analysis]
Number Citing Articles
1 Lapp MM, Lin G, Komin A, Andrews L, Knudson M, Mossman L, Raimondi G, Arciero JC. Modeling the Potential of Treg-Based Therapies for Transplant Rejection: Effect of Dose, Timing, and Accumulation Site. Transpl Int 2022;35:10297. [PMID: 35479106 DOI: 10.3389/ti.2022.10297] [Reference Citation Analysis]
2 Clancy CE, An G, Cannon WR, Liu Y, May EE, Ortoleva P, Popel AS, Sluka JP, Su J, Vicini P, Zhou X, Eckmann DM. Multiscale Modeling in the Clinic: Drug Design and Development. Ann Biomed Eng 2016;44:2591-610. [PMID: 26885640 DOI: 10.1007/s10439-016-1563-0] [Cited by in Crossref: 37] [Cited by in F6Publishing: 28] [Article Influence: 6.2] [Reference Citation Analysis]
3 Arciero JC, Maturo A, Arun A, Oh BC, Brandacher G, Raimondi G. Combining Theoretical and Experimental Techniques to Study Murine Heart Transplant Rejection. Front Immunol 2016;7:448. [PMID: 27872621 DOI: 10.3389/fimmu.2016.00448] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 0.2] [Reference Citation Analysis]
4 Fribourg M. A case for the reuse and adaptation of mechanistic computational models to study transplant immunology. Am J Transplant 2020;20:355-61. [PMID: 31562790 DOI: 10.1111/ajt.15623] [Reference Citation Analysis]