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Petros, J.A., Baumann, A.K., Ruiz-Pesini, E., Amin, M.B., Sun, C.Q., Hall, J., et al. (2005) mtDNA Mutations Increase Tumorigenicity in Prostate Cancer. Proceedings of the National Academy of Sciences of the United States of America, 102, 719-724.
https://doi.org/10.1073/pnas.0408894102

has been cited by the following article:

• TITLE: Understanding Model Independent Genetic Mutations through Trends in Increase in Entropy

  AUTHORS: Sage Copling, Maansi Srinivasan, Preet Sharma

  KEYWORDS: Statistical Physics, Mutations, Entropy, Energy

  JOURNAL NAME: Open Journal of Biophysics, Vol.12 No.3, July 31, 2022

  ABSTRACT: Introduction: A mutation, in general, can be defined as a change in the genetic sequence. Mutations can be changes as small as the substitution of a single DNA building block, or nucleotide base, with another nucleotide base. There can be larger mutations which can affect many genes on a chromosome. In this study we have tried to understand a normal mutation and a failed mutation from the point of view of entropy. We have shown that the entropy range of a normal mutation is less compared to the entropy range of a failed mutation. In this article we have plotted the increase of entropy of both types of mutations mentioned above. Statistical Physics of Partition Function and Entropy: In this section we have used statistical physics to define the partition function of an ensemble. Based on the partition function we have expressed how to calculate physical quantities such as average energy and entropy. Model Independent Mutation Entropy: The entropy of all processes increases. This is true even for biological systems. We have shown the difference between the entropy of a successful mutation and a failed mutation. Conclusion: In conclusion we have shown how the entropy of a successful mutation differs from that of a failed mutation. This opens up future research opportunities where we can apply this to specific biological systems.