Quantum-Mechanical Modeling of Mutations, Aging, Evolution, Tumor, and Cancer Development

Abstract

In this chapter, we will describe the quantum-mechanical models to accurately describe the process of creation of spontaneous, induced, and adaptive mutations. These models will be used to describe the processes of evolution and aging. The various theories of quantum evolution and epievolution will be studied as well. We then describe the Markovian chain-like classical and quantummechanical modeling of mutations and aging. In the same section, the hybrid quantum-classical biological channel model with memory is described as well. After that, various classical, semiclassical, and quantum models of cancer development are studied. The final section concludes the chapter. Quantum-Mechanical and Quantum Mechanics-Like Models for Mutations and EvolutionWe have already discussed the role of mutations in evolution process in Chap. 3; see Sect. 3.4. Based on several recent publications [1][2][3][4][5][6][7][8][9][10][11][12], it has become evident that both Darwinian type of evolution (random mutations followed by selection process) [13] and Lamarckian type of evolution (selected mutations beneficial to the organism) [14] are important. The modernized Lamarckian mechanism, which can also be called neo-Lamarckism, can be described as follows: environmental factors are introducing genomic changes, the mutations are targeted to specific genes, and the mutations provide the adaptation to the original cause. Clearly, this mechanism is well aligned with adaptive mutation mechanism discussed in Sect. 4.3 of the previous chapter (see also [15][16][17][18][19][20][21][22]). The Darwinian mechanism of evaluation is less demanding as no specialized mechanism is required to direct the change of the relevant genomic locus and restrict it to the specific mutations.Based on mutation models we discussed in previous chapter as well as references [1][2][3][4][5][6][7][8][9][10][11][12], it appears that both mechanisms can contribute to the evolution. For low stress levels, the spontaneous mutations seem to be a dominant source to evolution, suggesting Darwinian evolution mode is more relevant. On the other hand, for strong stress levels, the adaptive mutations dominate, indicating that Lamarckian

Information Theory in Computational Biology: Where We Stand Today

“…Lastly, with recent advancements in quantum computations, Shannon’s classical information theory is paving the way for using quantum information theory with physics to further the understanding of biological systems. Active research is being pursued in many uses of quantum information theory, such as developing quantum biological channel models suitable for the study of quantum information transfer from DNA to proteins [ 208 ], quantum-mechanical modeling of spontaneous, induced, and adaptive mutations and their role in cancerous tumor developments [ 209 ] and using both classical and quantum error-correction coding in genetics and evolution [ 210 ]. We conjecture that information theory has a key role to play in many theoretical and application developments in these areas in the near future.…”

Progress in and Opportunities for Applying Information Theory to Computational Biology and Bioinformatics

“…Assessing human physiological and emotional states in more informative and accurate ways can be facilitated with Information Theory concepts, including mutual information [ 52 ]. Shannon’s classical Information Theory is being advanced toward the use of quantum Information Theory [ 37 ] for applications including studying quantum information transfer from DNA to proteins [ 53 ], quantum-mechanical modeling of mutations in cancer [ 54 ], and error-correction coding in genetics [ 55 ]. This editorial provides a brief overview of some key opportunities for advancing Computational Biology and Bioinformatics by applying Information Theory; a more comprehensive review of the progress and open challenges is available in [ 37 ].…”