Literature DB >> 23086852

Agent-based models of cellular systems.

Nicola Cannata1, Flavio Corradini, Emanuela Merelli, Luca Tesei.   

Abstract

Software agents are particularly suitable for engineering models and simulations of cellular systems. In a very natural and intuitive manner, individual software components are therein delegated to reproduce "in silico" the behavior of individual components of alive systems at a given level of resolution. Individuals' actions and interactions among individuals allow complex collective behavior to emerge. In this chapter we first introduce the readers to software agents and multi-agent systems, reviewing the evolution of agent-based modeling of biomolecular systems in the last decade. We then describe the main tools, platforms, and methodologies available for programming societies of agents, possibly profiting also of toolkits that do not require advanced programming skills.

Mesh:

Year:  2013        PMID: 23086852     DOI: 10.1007/978-1-62703-059-5_18

Source DB:  PubMed          Journal:  Methods Mol Biol        ISSN: 1064-3745


  4 in total

1.  Agent-based spatiotemporal simulation of biomolecular systems within the open source MASON framework.

Authors:  Gael Pérez-Rodríguez; Martín Pérez-Pérez; Daniel Glez-Peña; Florentino Fdez-Riverola; Nuno F Azevedo; Anália Lourenço
Journal:  Biomed Res Int       Date:  2015-03-22       Impact factor: 3.411

Review 2.  Microfluidic-Based Multi-Organ Platforms for Drug Discovery.

Authors:  Ahmad Rezaei Kolahchi; Nima Khadem Mohtaram; Hassan Pezeshgi Modarres; Mohammad Hossein Mohammadi; Armin Geraili; Parya Jafari; Mohsen Akbari; Amir Sanati-Nezhad
Journal:  Micromachines (Basel)       Date:  2016-09-08       Impact factor: 2.891

3.  A Computer Model of Oxygen Dynamics in the Cortex of the Rat Kidney at the Cell-Tissue Level.

Authors:  Vivien Aubert; Jacques Kaminski; François Guillaud; Thierry Hauet; Patrick Hannaert
Journal:  Int J Mol Sci       Date:  2019-12-11       Impact factor: 5.923

4.  Agent-based models for detecting the driving forces of biomolecular interactions.

Authors:  Stefano Maestri; Emanuela Merelli; Marco Pettini
Journal:  Sci Rep       Date:  2022-02-03       Impact factor: 4.379

  4 in total

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