Cancer Growth Inhibition Using Predictive Mathematical Models of Signaling Pathways

Authors

  • Aadil Rashid Sheergojri Department of Mathematics and Actuarial Science, B. S. Abdur Rahman Crescent Institute of Science and Technology Chennai, India
  • Pervaiz Iqbal Department of Mathematics and Actuarial Science, B. S. Abdur Rahman Crescent Institute of Science and Technology Chennai, India
  • Ashiq Mohd Ilyas Department of Mathematics and Actuarial Science, B. S. Abdur Rahman Crescent Institute of Science and Technology Chennai, India

DOI:

https://doi.org/10.6000/1929-6029.2021.10.12

Keywords:

Cancer Growth, Modeling, Signaling Pathways, Predictive Mathematical Models

Abstract

Cancer cells develop several hallmark changes over the progress of the tumor process. Cell assistance in multicellular organisms is regulated by the division of cell coordination by aggressive growth modulation. In this perspective, the use of molecular indicators triggering cell division is a mystery, because a cancer cell can manipulate any molecule that induces and helps growth, disturbing cellular assistance. An effective alteration proceeding to tumors must develop to be competitive, allowing a cancer cell to pass a signal resulting in better selection chances. The subjective simulation of physiological systems has become increasingly valuable in recent years, and there is now a wide range of mathematical models of signalling pathways that have contributed to some groundbreaking discoveries and hypotheses as to how this system works. Here we discuss various modeling methods and their application to the physiology of medical systems, focusing on the identification of parameters in ordinary differential equation models and their significance for forecasting cellular decisions in network modeling. In situations of global and local cell-to-cell rivalry, we quantify how this mechanism impacts a mutated cell's fixing chance of producing such a signal, and consider that this process will play a vital role in reducing cancer.

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Published

2021-10-28

How to Cite

Sheergojri, A. R., Iqbal, P., & Ilyas, A. M. (2021). Cancer Growth Inhibition Using Predictive Mathematical Models of Signaling Pathways. International Journal of Statistics in Medical Research, 10, 132–135. https://doi.org/10.6000/1929-6029.2021.10.12

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General Articles