Dynamical cascades, in a multi-scale decomposition, have been described in our study. It has been applied in different networked systems, in physics and neuroscience. We describe the genotype decomposition of multidimensional information within an atomic structure. The path integral of information propagation has been derived, making it suitable for quantum computing.

In this article, we reflect on a computation methodology and data analysis of the epigenetic mechanisms in gene packaging and expression. We propose a data analysis assistance tool in medical applications from the perspective of quantum biology.

The animate and the inanimate

Early work on the reversibility of the second law of thermodynamics comes from William Sidis. He wrote The Animate and the Inanimate (1925), expressing his thoughts on the origin of life, and cosmology.

He states:

Thus we come to the conclusion that life is as eternal as the inanimate, and is to be found universally, under varying conditions, as inanimate phenomena". In his view, life has always existed, and it has only changed through evolution. He also digresses on the Big Bang origin of the Universe.

This book presented an early theoretical description of universal cycles, what he called the first law of physics. Buckminster Fuller came to a similar conclusion in his book Synergetics: Explorations in the Geometry of Thinking (1975).

What is life?

In his book What is Life? (1944) Erwin Schrodinger introduces the concepts of negentropy and the aperiodic crystals containing genetic information in its configuration of covalent chemical bonds. This idea has been acknowledged as influential by Frances Crick and James Watson for discovering the genetic molecule, DNA. Richard Feynman called his equation - the Schrodinger's "life" equation.

Data analysis of genotype information memory and expression

We have derived a multi-scale method of polynomial complexity for data analysis, coding and control1-3. This computation method captures a physical model for the generation of the underlying data. A scaling property of an atomic structure has been introduced within the theory of stochastic resonance synergies5.

Sampling genotype information in triplets describes our approach to non-polynomial completeness solving. Such a computational problem is pervasive in life sciences, especially. Although the triplets reading approach results in generally chaotic dynamics, in a deterministic interpretation, the predictability of an outcome of the genotype expressions is given in probability, in our study. Similarly, this approach extends to the other networked complex systems1-3.

Epigenetic mechanisms affect how DNA is packed into chromosomes and the genes accessible for transcription. Dynamical cascades map multidimensional information in multiple scales. We propose here a research study on epigenetics with data analysis of DNA code expression in sequences of genotype triplets. We envision this methodology as a core to different applications in life sciences, from bioinformatics to cognitive psychology1-3.

Concluding remarks

In this article, we have reflected on a data analysis methodology of genotype information. From the perspective of quantum biology, maintaining a low entropy state is essential for a mind and body's well-being and functioning.

In addition to the DNA-repair mechanisms of an immune system, and other self-healing mechanisms, we propose data analysis assistance tools in medical treatments of health diseases and aging. In our view, the development of quantum computing technologies and data science of genotype information processing in proteomics could be a helpful tool in preventing future pandemics, as well.


1 Jovovic, M., and G. Fox, “Multi-dimensional data scaling – dynamical cascade approach”, Indiana University, 2007.
2 Jovovic, M., “Stochastic Resonance Synergetics – Quantum Information Theory for Multidimensional Scaling”, Journal of Quantum Information Science, 5/2:47-57, 2015.
3 Jovovic M., “Attention, Memories and Behavioral Data-driven Study”, Advances in Neurology and Neuroscience, 2019.