Akademik Veri Yönetim Sistemi
International Journal of Mathematical and Computational Methods, cilt.20, ss.30-38, 2026 (Hakemli Dergi)
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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.2BD1 = D-TThis 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