DNA Sequence Evolution through Integral Value Transformations

In deciphering the DNA structures, evolutions and functions, Cellular Automata (CA) do have a significant role. DNA can be thought of as a one-dimensional multi-state CA, more precisely four states of CA namely A, T, C, and G which can be taken as numerals 0, 1, 2 and 3. Earlier, G.Ch. Sirakoulis et al reported the DNA structure, evolution and function through quaternary logic one dimensional CA and the authors have found the simulation results of DNA evolutions with the help of only four linear CA rules. The DNA sequences which are produced through the CA evolutions, however, are seen by our research team not to exist in the established databases of various genomes although the initial seed (initial global state of CA) was taken from the database. This problem motivated us to study the DNA evolutions from a more fundamental point of view. Parallel to the CA paradigm we have devised an enriched set of discrete transformations which have been named as Integral Value Transformations (IVT). Interestingly, on applying the IVT systematically, we have been able to show that each of the DNA sequences at various discrete time instances in IVT evolutions can be directly mapped to a specific DNA sequence existing in the database. This has been possible through our efforts of getting quantitative mathematical parameters of the DNA sequences involving Fractals. Thus we have at our disposal some transformational mechanism between one DNA to another

Reverse-engineering of polynomial dynamical systems

Multivariate polynomial dynamical systems over finite fields have been studied in several contexts, including engineering and mathematical biology. An important problem is to construct models of such systems from a partial specification of dynamic properties, e.g., from a collection of state transition measurements. Here, we consider static models, which are directed graphs that represent the causal relationships between system variables, so-called wiring diagrams. This paper contains an algorithm which computes all possible minimal wiring diagrams for a given set of state transition measurements. The paper also contains several statistical measures for model selection. The algorithm uses primary decomposition of monomial ideals as the principal tool. An application to the reverse-engineering of a gene regulatory network is included. The algorithm and the statistical measures are implemented in Macaulay2 and are available from the authors

A Mathematical Model of Central Dogma of Molecular Biology employing a Novel Irrational-Integral-Imaginary (i3) Encoding and Numerical Approximation based on Cellular Automaton

Cellular Automaton (CA) is usually used to model the spatio-temporal evolution of dynamical systems. In this work, a special class of the same known as 'Outer-totalistic' Cellular Automaton is applied to examine if there is a rationale behind the correlation between 64 possible codons and the resulting 20 amino-acids. Also, an attempt is made to mathematically model the central dogma of molecular biology in an intelligible format, including transcription and translation. Results suggest that our irrational-integral-imaginary (i3) encoding approach forms not only a satisfactory basis for a mathematical model of translation of mRNA to protein but also that of transcription from ssDNA (single stranded DNA) to mRNA (messenger RNA)