Agent-based Modelling in Multicellular Systems Biology


Sara Montagna, Andrea Omicini

Data Analytics in Medicine: Concepts, Methodologies, Tools, and Applications, Ch. 20, pages 369-389
 2020
IGI Global
Reprint of {{pubTitle}}AbminmsbMabsbioenvbook2017{{/pubTitle}}

This chapter aims at discussing the content of multi-agent based simulation (MABS) applied to computational biology, i.e, to modelling and simulating biological systems by means of computational models, methodologies, and frameworks. In particular, the adoption of agent- based modelling (ABM) in the field of multicellular systems biology is explored, focussing on the challenging scenarios of developmental biology. After motivating why agent-based abstractions are critical in representing multicellular systems behaviour, MABS is discussed as the source of the most natural and appropriate mechanism for analysing the self-organising behaviour of systems of cells. As a case study, an application of MABS to the development of Drosophila Melanogaster is finally presented, which exploits the ALCHEMIST agent-based simulation platform.

 @incollection{abminmsb-dataanalyticsmedicinebook2020,
author = {Montagna, Sara and Omicini, Andrea},
booktitle = {Data Analytics in Medicine: Concepts, Methodologies, Tools, and Applications},
chapter = 20,
doi = {10.4018/978-1-7998-1204-3.ch020},
irisid = {11585/786747},
isbn = {9781799812043},
isbn-10 = {1799812049},
isbn-online = {9781799812050},
note = {Reprint},
pages = {369--389},
publisher = {IGI Global},
title = {Agent-based Modelling in Multicellular Systems Biology},
url = {https://www.igi-global.com/gateway/chapter/243121},
year = 2020

Publication

— authors

Sara Montagna, Andrea Omicini

— status

published

— sort

book chapter

Venue

— volume

Data Analytics in Medicine: Concepts, Methodologies, Tools, and Applications

— chapter

20

— pages

369-389

— publication date

2020

URLs

original page

Identifiers

— DOI

10.4018/978-1-7998-1204-3.ch020

— IRIS

11585/786747

— Scopus

2-s2.0-85137554410

— print ISBN

9781799812043

— online ISBN

9781799812050

— ISBN–10

1799812049

BibTeX

— BibTeX ID
abminmsb-dataanalyticsmedicinebook2020
— BibTeX category
incollection

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