AUTHORS: Radoslav Mavrevski, Metodi Traykov, Ivan Trenchev, Miglena Trencheva

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ABSTRACT: Mathematical models are commonly used in biological sciences. To understand complex biological systems such as cells, tissues, or others, it is not enough to identify and characterize only individual molecules in the system. It also is necessary to obtain a thorough understanding of the interaction between molecules and different pathways. Computational models help investigators to analyze systems, develop hypotheses to guide the design of new experimental tests. Known are mathematical methods referring to different categories of biological processes. Now, modeling approaches are essential for biologists, enabling them to analyze complex physiological processes. The aim of this study is to presents a step-by-step applying non-linear regression analysis for fast and effective data analysis in the biology. To achieve this aim is used non-linear regression analysis method by GraphPad Prism software and the modeling of specific experimental data taken from available literature. Nonlinear regression is an extremely useful tool in analyzing data, but choosing a model is a scientific decision based on biology, chemistry or physiology and etc. and not be based solely on the shape of the graph.

KEYWORDS: Mathematical models, fitting, model selection criteria, biological data

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