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  • LATEST MANUSCRIPTS IN Computational and Systems Oncology
  • Antara Biswas, Bassel Ghaddar, Gregory Riedlinger, Subhajyoti De. Inference on spatial heterogeneity in tumor microenvironment using spatial transcriptomics data. Computational and systems oncology. 2022, 2 (3):
    Cited : 8
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  • Phillip B Nicol, Dániel L Barabási, Kevin R Coombes, Amir Asiaee. An R package for visualizing and analyzing a spatial model of intratumor heterogeneity. Computational and systems oncology. 2022, 2 (2):
    Cited : 1
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  • Cavan P Bailey, Ruiping Wang, Mary Figueroa, Shaojun Zhang, Linghua Wang, Joya Chandra. Computational immune infiltration analysis of pediatric high-grade gliomas (pHGGs) reveals differences in immunosuppression and prognosis by tumor location. Computational and systems oncology. 2021, 1 (3):
    Cited : 3
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  • Khanh N Dinh, Roman Jaksik, Seth J Corey, Marek Kimmel. Predicting Time to Relapse in Acute Myeloid Leukemia through Stochastic Modeling of Minimal Residual Disease Based on Clonality Data. Computational and systems oncology. 2021, 1 (3):
    Cited : 6
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  • Kamaldeen Okuneye, Daniel Bergman, Jeffrey C Bloodworth, Alexander T Pearson, Randy F Sweis, Trachette L Jackson. A validated mathematical model of FGFR3-mediated tumor growth reveals pathways to harness the benefits of combination targeted therapy and immunotherapy in bladder cancer. Computational and systems oncology. 2021, 1 (2):
    Cited : 13
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  • Ataur Katebi, Daniel Ramirez, Mingyang Lu. Computational systems-biology approaches for modeling gene networks driving epithelial-mesenchymal transitions. Computational and systems oncology. 2021, 1 (2):
    Cited : 12
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  • Heiko Enderling, Olaf Wolkenhauer. Are all models wrong? Computational and systems oncology. 2020, 1 (1):
    Cited : 20
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