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Mathematical modelling in bioinformatics

Class at Faculty of Science |
MB151P133

Syllabus

Models and Simulations differences between observation, model, simulations and laboratory experiments simplification of reality where and how mistakes arise different approaches to modelling

Simple model of immunity - experiments with a given model compartments feed forward and feedback definition of entities, their relations with the proportion of abstraction description of the model by differential equations examining the behavior of the model and modulating its behavior application of the model to biological situations

Creation and description of the model students create/define a more advanced model definition of entities, their relations with the proportion of abstraction and uncertainties of natural language; formulation of the model in the graph, analysis of the behavior of the model

Generalization of interactions introduction to the taxonomy of behaviors of dynamic systems introduction to the chaos theory of dynamical systems emergent behavior of the system: definitions, properties, conditions

Generalization of models taxonomy of models: principles and borders multiagent systems: definition of agents and environments formulation of a multiagent approach to cell models and intercellular interactions classification of models by agent type (no state, with state, with model, with goal, learning) cellular automata and other models described by rules

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Annotation

The course is based on mathematical modelling and development of biological (especially cellular) structures and processes that are simulated in silico.

We will deal with: a) the basics of modelling and simulations, including various approaches (especially from the point of view of the compartments and their interactions), including suitable and appropriate mathematical background b) application of models to specific biological situations - according to articles

Students will try and explore: a) a simple continuous compartmental model of immunity and its behavior, including the classification of system developments b) connection of the model with the data c) formulation of the model and its implementation d) a more complex discrete cell model with applications to cell differentiation and chemotactic motion

The research is conducted both analytically (what and why is happening) and synthetically (creating a system of given properties).