Abstract
Recent research emphasises the significance of identifying the latent geometry—also known as the geometry underlying a complex network—which is determined by the manifold class, curvature, and dimension. Geometry’s explanation of the organisational principles of complex systems and the potential that network nodes might be categorised according to their distances in this geometry are what confers geometry its significance. In this study, we analysed the network of genes resulting differentially expressed as a consequence of the modulation of protein tyrosine phosphatase receptor type G (PTPRG) in chronic myeloid leukaemia (CML) cell model K562 transcriptome. We found that the latent geometry of this network is hyperbolic, and that clustering according to the angular coordinates of its nodes in hyperbolic space classifies genes by functional pathway classes.