Agent‐Based Modeling in Molecular Systems Biology

Bioessays 40 (7):1800020 (2018)
  Copy   BIBTEX

Abstract

Molecular systems orchestrating the biology of the cell typically involve a complex web of interactions among various components and span a vast range of spatial and temporal scales. Computational methods have advanced our understanding of the behavior of molecular systems by enabling us to test assumptions and hypotheses, explore the effect of different parameters on the outcome, and eventually guide experiments. While several different mathematical and computational methods are developed to study molecular systems at different spatiotemporal scales, there is still a need for methods that bridge the gap between spatially‐detailed and computationally‐efficient approaches. In this review, we summarize the capabilities of agent‐based modeling (ABM) as an emerging molecular systems biology technique that provides researchers with a new tool in exploring the dynamics of molecular systems/pathways in health and disease.

Links

PhilArchive



    Upload a copy of this work     Papers currently archived: 91,846

External links

Setup an account with your affiliations in order to access resources via your University's proxy server

Through your library

Similar books and articles

The Sum of the Parts: Large-Scale Modeling in Systems Biology.Fridolin Gross & Sara Green - 2017 - Philosophy, Theory, and Practice in Biology 9 (10).
Interview with Sydney Brenner.Soraya de Chadarevian - 2009 - Studies in History and Philosophy of Science Part C: Studies in History and Philosophy of Biological and Biomedical Sciences 40 (1):65-71.
Conceptual Challenges in the Theoretical Foundations of Systems Biology.Marta Bertolaso & Emanuele Ratti - 2018 - In Mariano Bizzarri (ed.), Systems Biology. New York: Springer, Humana Press. pp. 1-13.
Data without models merging with models without data.Ulrich Krohs & Werner Callebaut - 2007 - In Fred C. Boogerd, Frank J. Bruggeman, Jan-Hendrik S. Hofmeyr & Hans V. Westerhoff (eds.), Systems Biology: Philosophical Foundations. Elsevier. pp. 181--213.

Analytics

Added to PP
2018-06-13

Downloads
24 (#656,297)

6 months
3 (#973,855)

Historical graph of downloads
How can I increase my downloads?