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We report on a theoretical study of point mutations effects on charge transfer properties in the DNA sequence of the tumor-suppressor p53 gene. On the basis of effective single-strand or double-strand tight-binding models which simulate hole propagation along the DNA, a statistical analysis of charge transmission modulations associated with all possible point mutations is performed. We find that in contrast to non-cancerous mutations, mutation hotspots tend to result in significantly weaker {em changes of transmission properties}. This suggests that charge transport could play a significant role for DNA-repairing deficiency yielding carcinogenesis.
Gene-gene interactions have long been recognized to be fundamentally important to understand genetic causes of complex disease traits. At present, identifying gene-gene interactions from genome-wide case-control studies is computationally and methodo
We assess the impact of cell cycle noise on gene circuit dynamics. For bistable genetic switches and excitable circuits, we find that transitions between metastable states most likely occur just after cell division and that this concentration effect
The premise of genetic analysis is that a causal link exists between phenotypic and allelic variation. Yet it has long been documented that mutant phenotypes are not a simple result of a single DNA lesion, but rather are due to interactions of the fo
Modeling the effects of mutations on the binding affinity plays a crucial role in protein engineering and drug design. In this study, we develop a novel deep learning based framework, named GraphPPI, to predict the binding affinity changes upon mutat
Contrary to long-held views, recent evidence indicates that $textit{de novo}$ birth of genes is not only possible, but is surprisingly prevalent: a substantial fraction of eukaryotic genomes are composed of orphan genes, which show no homology with a