Formulating DNA Chains Using Effective Calculability


  • Syed Atif Ali Shah Northern University, Nowshera
  • Zafar Khan Northern University, Nowshera
  • Zubia Rauf Qurtuba University, Peshawar
  • Syed Asif Ali Shah Abasyn University, Peshawar


DNA Chains, DNA Modeling, Effective Calculability, Lambda Calculus, Turing Machine.


Nearly all computational algorithms are modeled as ‘Effective Calculability’ i.e Finite State Model and Lambda Calculus. Effectively calculable function Comprise of three parts: the info, the yield, and the finite state function or transition function. It takes stream of data as input and translates to specific output, as defined by transition function [1]. The aftereffect of this conversion is another flood of information or the yield. Both i.e info and yield information streams comprise of arrangements of characters and are known as strings. DNA exhibits a property of being a pattern of strings. Automatic machines like automata and Lambda Calculus or simply the Effective Calculability [8] can be an efficient approach to study these patterns. By the introduction of Effective Calculability we can express the pattern of DNA in much better way. The transition function runs stepwise each character of the information string to produce the output string. The transformations achieved by the transition function are relatively simple in nature. Complex computations and operations can be affected by linking together several Effective Calculability switches so that the output string of one switch becomes the input string of another switch.


. J.H. Holland, in: Automata, Languages, Development, A. Lindenmayer and G. Rozenberg, eds. (North-Holland, Amsterdam, 1976), pp. 385-404.

. R. Ransom, Computers and Embryos: Models in Developmental Biology (Wiley, New York, 1981), pp. 106-156, 184-189.

. B. Lewin, Gene Expression, vol. III, Plasmids and Phages (Wiley-Interscience, New York, 1977).

. L. Nover, M. Luckner and B. Parthier, ed., Cell Differentiation: Molecular Basis and Problems (Springer, New York, 1982).

. Razin and A.D. Riggs, Science 210 (1980) 604.

. S,B, Zimmerman, Ann. Rev. Biochem. 51 (1982) 395.

. L. Nover and H. Reinbothe, in: Cell Differentiation: Molecular Basis and Problems, L. Nover, M. Luckner and B. Parthier, eds. (Springer, New York, 1982), pp. 23-74.

. Effective Calculability and Unsolvability. /~sweiss/course_materials/csci265/Unsolvability.pdf

. R. Breathnach and P. Chambon, Ann. Rev. Biochem. (1981) 349.

. L. Gold, D. Pribnow, T. Schneider, S. Shmedling, B.S. Singer and G. Stormo, Ann. Rev. Microbiol. 35 (1981) 365.

. J. Fickett, Nucl. Acids Res. 10 (1982) 5303.

. W.B. Goad and M.I. Kanehisa, Nucl. Acids Res. 10 (1982) 247.

. L. Nover, in: Cell Differentiation: Molecular Basis and Problems, L. Nover, M. Luckner and B. Parthier, eds. (Springer, New York, 1982), pp. 99-256.

. T.F. Smith, M.S. Waterman and C. Burks, LANL Preprint LA-UR-83-1661 (1983) Los Alamos National Laboratory.

. Reengineering the Industrial Capability and Maturity Model Integration, Journal of Advances in Computer Engineering and Technology (JACET). Volume 4, Issue 3

. R.E. Dickerson and H.R. Drew, J. Mol. Biol. 149 (1981) 761.

. R.E. Dickerson, H.R. Drew, B.N. Conner, R.M. Wing, A.V. Fratini and M.L. Kopka, Science 216 (1982) 475.

. R.E. Dickerson and H.R. Drew, Proc. Natl. Acad. Sci. USA 78 (1981) 7318.

. W. Kabsch, C. Sander and E.N. Trifinov, Nucl. Acids Res. 10 (1982) 1097.

. R.E. Dickerson, J. Mol. Biol. 166 (1983) 419.




How to Cite

Shah, S. A. A., Khan, Z., Rauf, Z., & Shah, S. A. A. (2018). Formulating DNA Chains Using Effective Calculability. International Journal of Computer (IJC), 31(1), 100–107. Retrieved from