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AUTHOR(S): Hasan Keleş, Edanur Keleş
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TITLE RNA-seq Based Simulations and a Cellular-Evolutionary Analysis Framework for Hyper G-Matrices |
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ABSTRACT This study integrates Hyper G-matrix theory with RNA-seq analysis to distinguish quantitative scaling from qualitative structural changes in gene regulatory networks. The Hyper G-matrix condition (A-T = D1BD2) provides a mathematical foundation for testing whether biological differences arise from expression changes or network reorganization. Using a 4×4 simulation comparing normal and tumor tissues, we demonstrate that the Hyper-G test discriminates between conserved architecture (p=0.71) and network rewiring (p=0.004). The framework’s key contribution is separating parametric changes from topological reorganization, with implications for understanding cancer and evolution. Multi-dimensional analysis reveals how matrix properties translate to cellular phenotypes, establishing a new paradigm for genomic data analysis with applications in cancer research and evolutionary biology. |
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KEYWORDS Hyper G-matrix theory, Gene regulatory networks, RNA-seq analysis, Network rewiring, Cancer genomics |
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Cite this paper Hasan Keleş, Edanur Keleş. (2026) RNA-seq Based Simulations and a Cellular-Evolutionary Analysis Framework for Hyper G-Matrices. International Journal of Mathematical and Computational Methods, 11, 30-38 |
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