Abstract
In this communication, we introduce a general framework and discussion on the role of models and the modeling process in the field of biosciences. The objective is to sum up the common procedures during the formalization and analysis of a biological problem from the perspective of Systems Biology, which approaches the study of biological systems as a whole. We begin by presenting the definitions of (biological) system and model. Particular attention is given to the meaning of mathematical model within the context of biology. Then, we present the process of modeling and analysis of biological systems. Three stages are described in detail: conceptualization of the biological system into a model, mathematical formalization of the previous conceptual model and optimization and system management derived from the analysis of the mathematical model. All along this work the main features and shortcomings of the process are analyzed and a set of rules that could help in the task of modeling any biological system are presented. Special regard is given to the formative requirements and the interdisciplinary nature of this approach. We conclude with some general considerations on the challenges that modeling is posing to current biology.
Highlights
A theory has only the alternative of being right or wrong
It is a matter of fact that the ecumenical nature of the training required by the modeling task in biosciences has impaired this desired evolution
The paradigm shift that involves the incorporation of the integrative approach requires shaping and expanding the training base of the new bioscience graduates with elements that include a broad and solid background in mathematics, thermodynamics, and scientific computing, among other new disciplines, in addition to the classic as chemistry, genetics and bioinformatics
Summary
A theory has only the alternative of being right or wrong. A model has a third possibility: it may be right, but irrelevant. These processes occur in an open system as a result of the existence of multiple gradients far from the thermodynamic equilibrium, which in the end produce very complicated non-linear dynamics between the elements of the system (Prigogine, 1961) This situation has impaired the quantitative and dynamic approach to the understanding of biological systems through the use of mathematical models. The distinctive feature of Systems Biology is the concern with the organization and biological function This approach goes beyond the classical reductionist approach, where the researcher seeks to understand the systems by breaking them down into their constituent elements and analyzing them separately or, in a novel version of the old paradigm facilitated by the high throughput techniques, by collecting every piece of accessible information. A set of rules that help the modeling activity is presented together with some general considerations on the challenges that modeling currently poses
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