D. Kumar S - Department of Mathematics, University of Rajasthan, Jaipur-302004, India. - Department of Mathematics, Kyung Hee University, 26 Kyungheedae-ro, Dongdaemun-gu, Seoul, 02447, Korea. H. Nama - Department of Mathematics, University of Rajasthan, Near East Boulevard, PC: 99138, Jaipur-302004, India. D. Baleanu - Department of Computer Science and Mathematics, Lebanese American University, Beirut, Lebanon. - Institute of Space Sciences-Subsidiary of INFLPR, Magurele-Bucharest, Romania.
The approximate numerical approach for the system of coupled nonlinear ordinary differential equations (ODEs) of a biochemical reaction model is very important for biochemists and scientist working in the field of biochemistry and related issues. Within this article, two computational algorithms for numerically solving a biochemical reaction model with time-fractional derivatives are examined and compared. The first technique depends on the collocation method along with the shifted Jacobi operational matrix for fractional derivative defined in the Caputo sense, and using this technique, we created a system of algebraic equations from the given fractional model. Another approach is centered on the basic theorem of fractional calculus and the characteristics of Newton's polynomial interpolation (NPI). We use these two methods to compute solution for the fractional biochemical reaction model. The model's computational outcomes are compared by using the recommended techniques in this work. Graphical and tabular forms are used to confirm the reliability and effectiveness of both techniques and an excellent match is discovered.
D. Kumar S, H. Nama, D. Baleanu, Computational framework for analyzing fractional biochemical reaction model, Journal of Mathematics and Computer Science, 36 (2025), no. 2, 218--228
Kumar S D., Nama H., Baleanu D., Computational framework for analyzing fractional biochemical reaction model. J Math Comput SCI-JM. (2025); 36(2):218--228
Kumar S, D., Nama, H., Baleanu, D.. "Computational framework for analyzing fractional biochemical reaction model." Journal of Mathematics and Computer Science, 36, no. 2 (2025): 218--228
