Mathematical applications in computational biology

Mathematical approaches are increasingly used in the field of computational biology to describe, analyze, and predict complex biological phenomena at molecular, cellular and population scales.This study discusses the applications of mathematical tools in computational biology such as differential equations, integral equations, linear algebra, matrix computation, and numerical solution techniques.Mathematical representations are created to describe interactions in biological systems, changes over time, regulation and quantitative relationships in biological systems.The use of differential equations represents the temporal behavior, and integral formulations represent cumulative biological effects.Linear algebra enables high dimensional processing of biological data, representation of networks and estimation of parameters.Numerical methods allow to solve models that do not have an analytical solution.The integrated framework exemplifies the enhancement of biological insights, biological simulations and predictive analysis through the use of mathematical computation.The results highlight the need for mathematical methods to further the development of computational modelling, biological data analysis and interdisciplinary science research in contemporary computational biology studies.

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Publication Details

Journal
Journal of Interdisciplinary Mathematics
Published
2026-10-27
DOI
https://doi.org/10.47974/jim-2831
Primary Topic
Genomics and Phylogenetic Studies
Type
article
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article

Mathematical applications in computational biology

Amit Gaurav, Suhas Bhise, Bhawna Rajput, S. Gayathri et al.
3 links
Journal of Interdisciplinary Mathematics
Genomics and Phylogenetic Studies
article

Mathematical applications in computational biology

Amit Gaurav, Suhas Bhise, Bhawna Rajput, S. Gayathri, R. Harshini, Nimesh Raj
article en

Abstract

Mathematical approaches are increasingly used in the field of computational biology to describe, analyze, and predict complex biological phenomena at molecular, cellular and population scales.This study discusses the applications of mathematical tools in computational biology such as differential equations, integral equations, linear algebra, matrix computation, and numerical solution techniques.Mathematical representations are created to describe interactions in biological systems, changes over time, regulation and quantitative relationships in biological systems.The use of differential equations represents the temporal behavior, and integral formulations represent cumulative biological effects.Linear algebra enables high dimensional processing of biological data, representation of networks and estimation of parameters.Numerical methods allow to solve models that do not have an analytical solution.The integrated framework exemplifies the enhancement of biological insights, biological simulations and predictive analysis through the use of mathematical computation.The results highlight the need for mathematical methods to further the development of computational modelling, biological data analysis and interdisciplinary science research in contemporary computational biology studies.

Journal of Interdisciplinary MathematicsVol. 29(10)
Vinayaka Missions University (IN), Meenakshi Academy of Higher Education and Research (IN), Noida International University (IN), Rungta College of Engineering and Technology (IN), Vishwakarma Institute of Technology (IN), Chitkara University (IN)
Openalex Percentile: Top 22%
Genomics and Phylogenetic Studies
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Mathematical applications in computational biology — Amit Gaurav, Suhas Bhise, et al. · Journal of Interdisciplinary Mathematics (2026) | TGRS Research Map | TGRS