Deterministic Differential Equations

Paola Lecca; Angela Re; Adaoha Ihekwaba; Ivan Mura; Thanh-Phuong Nguyen

doi:10.1016/b978-0-08-100095-3.00005-6

Deterministic Differential Equations

Paola Lecca, Angela Re, Adaoha Ihekwaba, Ivan Mura, Thanh-Phuong Nguyen

Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

Abstract

A practical introduction to the concepts underlying the deterministic modeling of biological systems by coupled differential equations is addressed in this chapter. We present a timed interpretation of the occurrence of events in a biological system that well suits the encoding of qualitative information concerning the structure of networks of interacting components as well as the quantitative information obtained through “wet-laboratory” experiments. We first illustrate the basic rationale of the model specification process, supported by the presentation of a set of increasing complexity examples. We then proceed to describe the possibilities of analytical evaluation of model dynamics as well as the basic concepts underlying the simulative approaches, through application to relevant instances of biological systems.

Original language	English
Title of host publication	Computational Systems Biology
Subtitle of host publication	Inference and Modelling
Publisher	Elsevier
Chapter	5
Pages	67-98
Number of pages	32
Edition	1
ISBN (Print)	978-0-08-100095-3
DOIs	https://doi.org/10.1016/b978-0-08-100095-3.00005-6
Publication status	Published - 2016
Externally published	Yes

Publication series

Name	Computational Systems Biology

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10.1016/b978-0-08-100095-3.00005-6

Cite this

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AU - Re, Angela

AU - Ihekwaba, Adaoha

AU - Mura, Ivan

AU - Nguyen, Thanh-Phuong

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Y1 - 2016

N2 - A practical introduction to the concepts underlying the deterministic modeling of biological systems by coupled differential equations is addressed in this chapter. We present a timed interpretation of the occurrence of events in a biological system that well suits the encoding of qualitative information concerning the structure of networks of interacting components as well as the quantitative information obtained through “wet-laboratory” experiments. We first illustrate the basic rationale of the model specification process, supported by the presentation of a set of increasing complexity examples. We then proceed to describe the possibilities of analytical evaluation of model dynamics as well as the basic concepts underlying the simulative approaches, through application to relevant instances of biological systems.

AB - A practical introduction to the concepts underlying the deterministic modeling of biological systems by coupled differential equations is addressed in this chapter. We present a timed interpretation of the occurrence of events in a biological system that well suits the encoding of qualitative information concerning the structure of networks of interacting components as well as the quantitative information obtained through “wet-laboratory” experiments. We first illustrate the basic rationale of the model specification process, supported by the presentation of a set of increasing complexity examples. We then proceed to describe the possibilities of analytical evaluation of model dynamics as well as the basic concepts underlying the simulative approaches, through application to relevant instances of biological systems.

UR - https://www.mendeley.com/catalogue/8776163d-d1f8-300a-a8d1-775b52a2b615/

UR - https://www.sciencedirect.com/book/9780081000953/computational-systems-biology

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SN - 978-0-08-100095-3

T3 - Computational Systems Biology

SP - 67

EP - 98

BT - Computational Systems Biology

PB - Elsevier

ER -

Deterministic Differential Equations

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