Mathematical modeling of biological systems

Abstract

Mathematical and computational models are increasingly used to help interpret biomedical data produced by high-throughput genomics and proteomics projects. The application of advanced computer models enabling the simulation of complex biological processes generates hypotheses and suggests experiments. Appropriately interfaced with biomedical databases, models are necessary for rapid access to, and sharing of knowledge through data mining and knowledge discovery approaches.

Bayesian immunological model development from the literature: Example investigation of recent thymic emigrants

“…(Motta and Pappalardo, 2013). As illustrated in Section 2.1, model development should be governed by immunological theory.…”

“…Formulation is the first step in which biological concepts are formalized as mathematical constructs, whereas development is the more encompassing, iterative process of formulation, testing, revision of formulation, etc. See Motta and Pappalardo (2013) for a general overview of the process of model development. The statistical aspects of model development are discussed in Section 6.4.…”

Engineering solutions for open microalgae mass cultivation and realistic indoor simulation of outdoor environments

“…Model refinements can be variations of, e.g. scope, assumptions, equations, parameters, or algorithms [113,114]. Model validation is the determination of the degree of accuracy to which a model represents reality [115].…”

“…Once the accuracy is as desired, both biological and engineering models have been validated and an improved reactor or process design has been found using a model-based approach. More information regarding various aspects of model-based development of bioprocesses can be found in specialized literature [21,110,114,115,117,118]. Huesemann et al [119] gave a short overview of published models for photoautotrophic microalgae cultivation, noting that despite experimental model validation is essential, some models were published without validation or were of such a complex design that correct validation is almost impossible.…”

Simulation-based optimization of radiotherapy: Agent-based modeling and reinforcement learning

“…The overall behavior of the system arises from the collective local behavior of the involved entities [8]. In Agent-based models more detailed description of the organism is required and the population dynamics may eventually be extracted from the dynamic response of each entity [27]. Agent-based modeling offers a natural description of a system [4].…”